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Sökning: L773:0888 3270 OR L773:1096 1216

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1.
  • Andrén, Linus, et al. (författare)
  • Identification of Dynamic Properties of Boring Bar Vibrations in a Continuous Boring Operation
  • 2004
  • Ingår i: Mechanical systems and signal processing. - : Academic Press. - 0888-3270 .- 1096-1216. ; 18:4, s. 869-901
  • Tidskriftsartikel (refereegranskat)abstract
    • Vibrations in internal turning operations are usually a cumbersome part of the manufacturing process. This article focuses on the boring bar vibrations. Boring bar vibrations in alloyed steel, stainless steel and cast iron have been measured in both the cutting speed direction and the cutting depth direction with the aid of accelerometers. The dynamic response of a boring bar seem to be a time varying process that exhibits non-linear behaviour. The process is influenced by non-stationary parameters that are not under the control of the operator or experimenter. The vibrations are clearly dominated by the first resonance frequency in one of the two directions of the boring bar. The problem with force modulation in rotary machinery, which appears as side band terms in the spectrum, is also addressed. Furthermore, the resonance frequencies of the boring bar are correlated to an Euler-Bernoulli beam model.
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2.
  • Abdeljaber, Osama, et al. (författare)
  • Optimization of linear zigzag insert metastructures for low-frequency vibration attenuation using genetic algorithms
  • 2017
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 84:Part A, s. 625-641
  • Tidskriftsartikel (refereegranskat)abstract
    • Vibration suppression remains a crucial issue in the design of structures and machines. Recent studies have shown that with the use of metamaterial inspired structures (or metastructures), considerable vibration attenuation can be achieved. Optimization of the internal geometry of metastructures maximizes the suppression performance. Zigzag inserts have been reported to be efficient for vibration attenuation. It has also been reported that the geometric parameters of the inserts affect the vibration suppression performance in a complex manner. In an attempt to find out the most efficient parameters, an optimization study has been conducted on the linear zigzag inserts and is presented here. The research reported in this paper aims at developing an automated method for determining the geometry of zigzag inserts through optimization. This genetic algorithm based optimization process searches for optimal zigzag designs which are properly tuned to suppress vibrations when inserted in a specific host structure (cantilever beam). The inserts adopted in this study consist of a cantilever zigzag structure with a mass attached to its unsupported tip. Numerical simulations are carried out to demonstrate the efficiency of the proposed zigzag optimization approach.
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3.
  • Abdollahpouri, Mohammad, 1985, et al. (författare)
  • Adaptive vibration attenuation with globally convergent parameter estimation
  • 2019
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 114, s. 512-527
  • Tidskriftsartikel (refereegranskat)abstract
    • Parameter estimation problems can be nonlinear, even if the dynamics are expressed by a linear model. The extended Kalman filter (EKF), even though it is one of the most popular nonlinear estimation techniques, may not converge without sufficient a priori information. This paper utilizes a globally convergent nonlinear estimation method the double Kalman filter (DKF) for a vibrating cantilever beam. A globally valid linear time-varying (LTV) model is required by the first stage of the DKF depending on some conditions on input and output excitation. Without considering noise, this LW model provides the first stage and is globally equivalent to the nonlinear system. Since the neglected input and output noises can degrade the quality of estimation, the second stage linearizes the nonlinear dynamics, utilizing the nominally globally convergent estimate of the first stage, and improves the quality of estimation. Both estimation methods were applied to a cantilever beam setup in real-time. An adaptive linear quadratic regulator utilizes the estimated parameters to attenuate unknown transient disturbances. Different scenarios have been explored, providing a fair comparison between EKF and DKF. These methods have been implemented on an embedded ARM-based microcontroller unit and illustrates improved convergent properties of the DKF over the EKF. The global stability of the DKF is verified and it has been observed that it needs twice the computational cost of the EKF.
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4.
  • Abrahamsson, Thomas, 1956, et al. (författare)
  • Finite element model calibration using frequency responses with damping equalization
  • 2015
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 62-63, s. 218-234
  • Tidskriftsartikel (refereegranskat)abstract
    • Model calibration is a cornerstone of the finite element verification and validation procedure, in which the credibility of the model is substantiated by positive comparison with test data. The calibration problem, in which the minimum deviation between finite element model data and experimental data is searched for, is normally characterized as being a large scale optimization problem with many model parameters to solve for and with deviation metrics that are nonlinear in these parameters. The calibrated parameters need to be found by iterative procedures, starting from initial estimates. Sometimes these procedures get trapped in local deviation function minima and do not converge to the globally optimal calibration solution that is searched for. The reason for such traps is often the multi-modality of the problem which causes eigenmode crossover problems in the iterative variation of parameter settings. This work presents a calibration formulation which gives a smooth deviation metric with a large radius of convergence to the global minimum. A damping equalization method is suggested to avoid the mode correlation and mode pairing problems that need to be solved in many other model updating procedures. By this method, the modal damping of a test data model and the finite element model is set to be the same fraction of critical modal damping. Mode pairing for mapping of experimentally found damping to the finite element model is thus not needed. The method is combined with model reduction for efficiency and employs the Levenberg-Marquardt minimizer with randomized starts to achieve the calibration solution. The performance of the calibration procedure, including a study of parameter bias and variance under noisy data conditions, is demonstrated by two numerical examples.
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5.
  • Adolfsson, Stefan, et al. (författare)
  • Automatic detection of burn-through in GMA welding using a parametric model
  • 1996
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 10:5, s. 633-651
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper addresses the problem of automatic detection of burn-through in weld joints. Gas metal arc (GMA) welding with pulsed current is used, and welding voltage and current are recorded. As short-circuitings are common between the welding electrode and the work piece during burn-through, a short-circuit detector is developed to detect these events. To detect another specific characteristic of burn-through - this detector is combined with a square-law detector. This second detector is based on a non-linear modification of an autoregressive model with extra input (ARX-model) of the welding process. The results obtained from this compound detector indicate that it is possible to detect burn-through in the welds automatically. The work also indicates that it is possible to design an on-line monitoring system for robotic GMA welding.
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6.
  • Ambrozinski, Lukasz, et al. (författare)
  • Self-focusing Lamb waves based on the decomposition of the time-reversal operator using time-frequency representation
  • 2012
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 27, s. 337-349
  • Tidskriftsartikel (refereegranskat)abstract
    • Active ultrasonic arrays are very useful for structural health monitoring (SHM) of large plate-like structures. Large areas of a plate can be monitored from a fixed position but it normally requires precise information on material properties. Self-focusing methods can perform well without the exact knowledge of a medium and array parameters. In this paper a method for selective focusing of Lamb waves will be presented. The algorithm is an extension of the DORT method (French acronym for decomposition of time-reversal operator) where the continuous wavelet transform (CWT) is used for the time-frequency representation (TFR) of nonstationary signals instead of the discrete Fourier transform. The performance of the methods is compared and verified in the paper using both simulated and experimental data. It is shown that the extension of the DORT method with the use of TFR considerably improved its resolving ability. To experimentally evaluate the performance of the proposed method, a linear array of small piezoelectric transducers attached to an aluminum plate was used to obtain interelement responses, required for beam self-focusing on targets present in the plate. The array was used for the transmission of signals calculated with the DORT-CWT algorithm. To verify the self-focusing effect the backpropagated field generated in the experiment was sensed using laser scanning vibrometer.
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7.
  • Andrén, Linus, et al. (författare)
  • Identification of Motion of Cutting Tool Vibration in a Continuous Boring Operation : Correlation to structural Properties
  • 2004
  • Ingår i: Mechanical systems and signal processing. - : Academic Press, UK. - 0888-3270 .- 1096-1216. ; 18:4, s. 903-27
  • Tidskriftsartikel (refereegranskat)abstract
    • The internal turning operation has a history of being a cumbersome metal working process as vibration in boring operations is usually inevitable. In this article, the deflection shapes and/or mode shapes as well as the resonance frequencies of a boring bar have been put under scrutiny. Three methods have been used in order to investigate dynamic properties of a clamped boring bar: a theoretical Euler-Bernoulli beam model, an experimental modal analysis and an operating deflection shape analysis. \\ The results indicate a correlation between the shapes of the deflection shapes and/or mode shapes produced by the three different analysis methods. On the other hand, the orientation of the forced deflection shapes and/or mode shapes and the resonance frequencies demonstrates differences between the three methods. During continuous cutting, it is demonstrated that the bending motion of the first two resonance frequencies is to a large extent in the cutting speed direction.
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8.
  • Ashwear, Nasseradeen, 1968-, et al. (författare)
  • Vibration health monitoring for tensegrity structures
  • 2017
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 85, s. 625-637
  • Tidskriftsartikel (refereegranskat)abstract
    • Tensegrities are assembly structures, getting their equilibrium from the interaction between tension in cables and compression in bars. During their service life, slacking'in their cables and nearness to buckling in their bars need to be monitored to avoid a sudden collapse. This paper discusses how to design the tensegrities to make them feasible for vibrational health monitoring methods. Four topics are discussed; suitable finite elements formulation, pre-measurements analysis to find the locations of excitation and sensors for the interesting modes, the effects from some environmental conditions, and the pre-understanding of the effects from different slacking scenarios.
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9.
  • Avci, Onur, et al. (författare)
  • A review of vibration-based damage detection in civil structures : from traditional methods to Machine Learning and Deep Learning applications
  • 2021
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 147
  • Tidskriftsartikel (refereegranskat)abstract
    • Monitoring structural damage is extremely important for sustaining and preserving the service life of civil structures. While successful monitoring provides resolute and staunch information on the health, serviceability, integrity and safety of structures; maintaining continuous performance of a structure depends highly on monitoring the occurrence, formation and propagation of damage. Damage may accumulate on structures due to different environmental and human-induced factors. Numerous monitoring and detection approaches have been developed to provide practical means for early warning against structural damage or any type of anomaly. Considerable effort has been put into vibration-based methods, which utilize the vibration response of the monitored structure to assess its condition and identify structural damage. Meanwhile, with emerging computing power and sensing technology in the last decade, Machine Learning (ML) and especially Deep Learning (DL) algorithms have become more feasible and extensively used in vibration-based structural damage detection with elegant performance and often with rigorous accuracy. While there have been multiple review studies published on vibration-based structural damage detection, there has not been a study where the transition from traditional methods to ML and DL methods are described and discussed. This paper aims to fulfill this gap by presenting the highlights of the traditional methods and provide a comprehensive review of the most recent applications of ML and DL algorithms utilized for vibration-based structural damage detection in civil structures.
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10.
  • Baissa, Wirtu, et al. (författare)
  • Vibration-based structural damage identification using wavelet transform
  • 2008
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 1096-1216 .- 0888-3270. ; 22:5, s. 1194-1215
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents a new damage identification technique based on the statistical moments of the energy density function of the vibration responses in the time-scale (or time-frequency) domain. The continuous wavelet transform is first conducted to decompose the vibration responses into discrete energy distributions as a joint function of time and scale. The principal structural response features are then extracted from the energy density functions using moments. Consequently, the zeroth-order moment (ZOM) known as the total energy of the joint density function is computed at each measurement grid point for the pre-damage and post-damage states and is then implemented for detection and localization of damage in a concrete plate model and in a steel plate girder of a bridge structure. The significant contribution is that the wavelet coefficients are transformed into a new damage identification parameter in the space domain which is considered to be a novel application of the wavelet analysis coefficients. The major advantage is that the time-frequency analysis conducted using the wavelet transform provides a powerful tool to characterize deterministic as well as random (stationary and non-stationary) responses and can be used to detect slight changes in the response characteristics and local variations. Finally, comparison of the results obtained from the proposed method and those obtained from existing non-model-based damage identification techniques shows that the proposed method is more sensitive to damage than these other methods.
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11.
  • Baptista, Marcia L., et al. (författare)
  • More effective prognostics with elbow point detection and deep learning
  • 2021
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 146
  • Tidskriftsartikel (refereegranskat)abstract
    • Prior to failure, most systems exhibit signs of changed characteristics. The early detection of this change is important to remaining useful life estimation. To have the ability to detect the inflection point or “elbow point” of an asset, i.e. the point of the degradation curve that marks the transition from nominal to faulty condition, can enable more sophisticated prognostics because this divide and conquer tactic allows the prediction to focus on the window before failure when significant changes are being expected. In this work, we compare prognostics with and without change point detection. We use different recurrent neural network techniques (standard recurrent neural network, long short-term memory and gated recurrent unit) to find the elbow point location. The actual estimation of the remaining time to failure is based on the echo state network, a state-of-the-art approach in prognostics. Two different experiments are performed on simulated data obtained from NASA Ames prognostics repository. We first compare the performance of the elbow point detectors based on recurrent neural networks against three baseline models: the Z-test, multi-layer perceptron and random forests. Results indicate that recurrent neural networks can outperform the baseline approaches. In the second experiment, the best elbow detection model, the gated recurrent unit, is integrated within an echo state network, with a significant increase in overall performance in terms of remaining useful life estimation.
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12.
  • Cahill, Paul, et al. (författare)
  • Vibration energy harvesting based monitoring of an operational bridge undergoing forced vibration and train passage
  • 2018
  • Ingår i: Mechanical systems and signal processing. - : Academic Press. - 0888-3270 .- 1096-1216. ; 106, s. 265-283
  • Tidskriftsartikel (refereegranskat)abstract
    • The application of energy harvesting technology for monitoring civil infrastructure is a bourgeoning topic of interest. The ability of kinetic energy harvesters to scavenge ambient vibration energy can be useful for large civil infrastructure under operational conditions, particularly for bridge structures. The experimental integration of such harvesters with full scale structures and the subsequent use of the harvested energy directly for the purposes of structural health monitoring shows promise. This paper presents the first experimental deployment of piezoelectric vibration energy harvesting devices for monitoring a fullscale bridge undergoing forced dynamic vibrations under operational conditions using energy harvesting signatures against time. The calibration of the harvesters is presented, along with details of the host bridge structure and the dynamic assessment procedures. The measured responses of the harvesters from the tests are presented and the use the harvesters for the purposes of structural health monitoring (SHM) is investigated using empirical mode decomposition analysis, following a bespoke data cleaning approach. Finally, the use of sequential Karhunen Loeve transforms to detect train passages during the dynamic assessment is presented. This study is expected to further develop interest in energy harvesting based monitoring of large infrastructure for both research and commercial purposes.
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13.
  • Cantero, Daniel, et al. (författare)
  • Time-frequency analysis of railway bridge response in forced vibration
  • 2016
  • Ingår i: Mechanical systems and signal processing. - : Academic Press. - 0888-3270 .- 1096-1216. ; 76-77, s. 518-530
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper suggests the use of the Continuous Wavelet Transform in combination with the Modified Littlewood-Paley basis to analyse bridge responses exited by traversing trains. The analysis provides an energy distribution map in the time-frequency domain that offers a better resolution compared to previous published studies. This is demonstrated with recorded responses of the Skidträsk Bridge, a 36 m long composite bridge located in Sweden. It is shown to be particularly useful to understand the evolution of the energy content during a vehicle crossing event. With this information it is possible to distinguish the effect of several of the governing factors involved in the dynamic response including vehicle's speed and axle configuration as well as non-linear behaviour of the structure.
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14.
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15.
  • Cuenca, J., et al. (författare)
  • Deterministic and statistical methods for the characterisation of poroelastic media from multi-observation sound absorption measurements
  • 2022
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 163
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper proposes a framework for the estimation of the transport and elastic properties of open-cell poroelastic media based on sound absorption measurements. The sought properties are the Biot-Johnson-Champoux-Allard model parameters, namely five transport parameters, two elastic properties and the mass density, as well as the sample thickness. The methodology relies on a multi-observation approach, consisting in combining multiple independent measurements into a single dataset, with the aim of over-determining the problem. In the present work, a poroelastic sample is placed in an impedance tube and tested in two loading conditions, namely in a rigid-backing configuration and coupled to a resonant expansion chamber. Given the nonmonotonic nature of the experimental data, an incremental parameter estimation procedure is used in order to guide the model parameters towards the global solution without terminating at local minima. A statistical inversion approach is also discussed, providing refined point estimates, uncertainty ranges and parameter correlations. The methodology is applied to the characterisation of a sample of melamine foam and provides estimates of all nine parameters with compact uncertainty ranges. It is shown that the model parameters are retrieved with a lower uncertainty in the multi-observation case, as compared with a single-observation case. The method proposed here does not require prior knowledge of the thickness or any of the properties of the sample, and can be carried out with a standard two-microphone impedance tube.
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16.
  • Decuyper, J., et al. (författare)
  • Retrieving highly structured models starting from black-box nonlinear state-space models using polynomial decoupling
  • 2021
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 146
  • Tidskriftsartikel (refereegranskat)abstract
    • Nonlinear state-space modelling is a very powerful black-box modelling approach. However powerful, the resulting models tend to be complex, described by a large number of parameters. In many cases interpretability is preferred over complexity, making too complex models unfit or undesired. In this work, the complexity of such models is reduced by retrieving a more structured, parsimonious model from the data, without exploiting physical knowledge. Essential to the method is a translation of all multivariate nonlinear functions, typically found in nonlinear state-space models, into sets of univariate nonlinear functions. The latter is computed from a tensor decomposition. It is shown that typically an excess of degrees of freedom are used in the description of the nonlinear system whereas reduced representations can be found. The method yields highly structured state-space models where the nonlinearity is contained in as little as a single univariate function, with limited loss of performance. Results are illustrated on simulations and experiments for: the forced Duffing oscillator, the forced Van der Pol oscillator, a Bouc-Wen hysteretic system, and a Li-Ion battery model. (C) 2020 Elsevier Ltd. All rights reserved.
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17.
  • Ericsson, Stefan, et al. (författare)
  • Towards automatic detection of local bearing defects in rotating machines
  • 2005
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 19:3, s. 509-535
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper we derive and compare several different vibration analysis techniques for automatic detection of local defects in bearings. Based on a signal model and a discussion on to what extent a good bearing monitoring method should trust it, we present several analysis tools for bearing condition monitoring and conclude that wavelets are especially well suited for this task. Then we describe a large-scale evaluation of several different automatic bearing monitoring methods using 103 laboratory and industrial environment test signals for which the true condition of the bearing is known from visual inspection. We describe the four best performing methods in detail (two wavelet-based, and two based on envelope and periodisation techniques). In our basic implementation, without using historical data or adapting the methods to (roughly) known machine or signal parameters, the four best methods had 9-13% error rate and are all good candidates for further fine-tuning and optimisation. Especially for the wavelet-based methods, there are several potentially performance improving additions, which we finally summarise into a guiding list of suggestion.
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18.
  • Georgoulas, Georgios, et al. (författare)
  • Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition
  • 2013
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 41:1-2, s. 510-525
  • Tidskriftsartikel (refereegranskat)abstract
    • Aiming at more efficient fault diagnosis, this research work presents an integrated anomaly detection approach for seeded bearing faults. Vibration signals from normal bearings and bearings with three different fault locations, as well as different fault sizes and loading conditions are examined. The Empirical Mode Decomposition and the Hilbert Huang transform are employed for the extraction of a compact feature set. Then, a hybrid ensemble detector is trained using data coming only from the normal bearings and it is successfully applied for the detection of any deviation from the normal condition. The results prove the potential use of the proposed scheme as a first stage of an alarm signalling system for the detection of bearing faults irrespective of their loading condition.
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19.
  • Georgoulas, Georgios, et al. (författare)
  • Rolling element bearings diagnostics using the Symbolic Aggregate approXimation
  • 2015
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 60, s. 229-242
  • Tidskriftsartikel (refereegranskat)abstract
    • Rolling element bearings are a very critical component in various engineering assets. Therefore it is of paramount importance the detection of possible faults, especially at an early stage, that may lead to unexpected interruptions of the production or worse, to severe accidents. This research work introduces a novel, in the field of bearing fault detection, method for the extraction of diagnostic representations of vibration recordings using the Symbolic Aggregate approXimation (SAX) framework and the related intelligent icons representation. SAX essentially transforms the original real valued time-series into a discrete one, which is then represented by a simple histogram form summarizing the occurrence of the chosen symbols/words. Vibration signals from healthy bearings and bearings with three different fault locations and with three different severity levels, as well as loading conditions, are analyzed. Considering the diagnostic problem as a classification one, the analyzed vibration signals and the resulting feature vectors feed simple classifiers achieving remarkably high classification accuracies. Moreover a sliding window scheme combined with a simple majority voting filter further increases the reliability and robustness of the diagnostic method. The results encourage the potential use of the proposed methodology for the diagnosis of bearing faults
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20.
  • Gibanica, Mladen, 1988, et al. (författare)
  • Identification of physically realistic state-space models for accurate component synthesis
  • 2020
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 145
  • Tidskriftsartikel (refereegranskat)abstract
    • For components that are difficult to model with conventional analytical or numerical tools, experimentally derived state-space models can instead be used in system synthesis. For successful state-space synthesis, a physically realistic model must be identified. For this purpose, a hybrid first- and second-order system description is used here as the basis for identification. In the identification procedure, a physically motivated rigid body rank constraint is imposed together with a reciprocity constraint. The two constraints are enforced during a re-estimation phase of the state-space matrices following after a traditional state-space subspace identification phase. In this paper, two complex and modally dense industrial components are combined into a dynamical system. An experimental model of a car body-in-white structure is identified. The identified subsystem model is coupled with a finite element model of a rear subframe in a system synthesis. The two subsystems are attached through four rubber bushings modelled by finite element procedures. It is shown that the experimental-analytical assembly successfully predicts the reference measured system, with higher accuracy than what could be achieved with a model based solely on finite elements. It is also shown that synthesis with individually calibrated rear subframe models can capture the variability in the coupled system.
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21.
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22.
  • Giordano, Giuseppe, 1985, et al. (författare)
  • Black- and white-box approaches for cascaded tanks benchmark system identification
  • 2018
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 108, s. 387-397
  • Tidskriftsartikel (refereegranskat)abstract
    • This contribution consists of the identification and comparison of different models for a non-linear system: the Cascaded Tanks system. The identification of this system is challenging due to the combination of soft and hard non-linearities. Model structures with different levels of flexibility and prior knowledge are compared. The most simple ones are linear black-box models. They are extended to become non-linear black-box models, whose performances are compared with the linear ones. A second track is the investigation of a series of models with increasing complexity based on physical prior knowledge. Results show that while linear black-box models perform good in prediction, a fairly precise description of the non-linear effects is needed to achieve good performances in simulation. All models have been estimated and validated using benchmark data from a real cascaded tanks system. The contribution represents also an overview on how standard modelling techniques perform on a real identification problem.
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23.
  • Grip, Niklas, et al. (författare)
  • Sensitivity-based model updating for structural damage identification using total variation regularization
  • 2017
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 84:A, s. 365-383
  • Tidskriftsartikel (refereegranskat)abstract
    • Sensitivity-based Finite Element Model Updating (FEMU) is one of the widely accepted techniques used for damage identification in structures. FEMU can be formulated as a numerical optimization problem and solved iteratively making automatic updating of the unknown model parameters by minimizing the difference between measured and analytical structural properties. However, in the presence of noise in the measurements, the updating results are usually prone to errors. This is mathematically described as instability of the damage identification as an inverse problem. One way to resolve this problem is by using regularization. In this paper, we compare a well established interpolation-based regularization method against methods based on the minimization of the total variation of the unknown model parameters. These are new regularization methods for structural damage identification. We investigate how using Huber and pseudo Huber functions in the definition of total variation affects important properties of the methods. For instance, for well-localized damages the results show a clear advantage of the total variation based regularization in terms of the identified location and severity of damage compared with the interpolation-based solution.For a practical test of the proposed method we use a reinforced concrete plate. Measurements and analysis were performed first on an undamaged plate, and then repeated after applying four different degrees of damage.
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24.
  • Göransson, Peter, 1959-, et al. (författare)
  • Parameter estimation in modelling frequency response of coupled systems using a stepwise approach
  • 2019
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 126, s. 161-175
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper studies the problem of parameter estimation in resonant, acoustic fluid-structure interaction problems over a wide frequency range. Problems with multiple resonances are known to be subjected to local minima, which represents a major challenge in the field of parameter identification. We propose a stepwise approach consisting in subdividing the frequency spectrum such that the solution to a low-frequency subproblem serves as the starting point for the immediately higher frequency range. In the current work, two different inversion frameworks are used. The first approach is a gradient-based deterministic procedure that seeks the model parameters by minimising a cost function in the least squares sense and the second approach is a Bayesian inversion framework. The latter provides a potential way to assess the validity of the least squares estimate. In addition, it presents several advantages by providing invaluable information on the uncertainty and correlation between the estimated parameters. The methodology is illustrated on synthetic measurements with known design variables and controlled noise levels. The model problem is deliberately kept simple to allow for extensive numerical experiments to be conducted in order to investigate the nature of the local minima in full spectrum analyses and to assess the potential of the proposed method to overcome these. Numerical experiments suggest that the proposed methods may present an efficient approach to find material parameters and their uncertainty estimates with acceptable accuracy.
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25.
  • Johansson, Anders, 1982, et al. (författare)
  • A method for improving test rig performance using passive components
  • 2015
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 52-53:1, s. 614-627
  • Tidskriftsartikel (refereegranskat)abstract
    • The time waveform replication (TWR) algorithm is presently used in industry for calculating the actuation force needed to replicate a certain reference sensor output in a test rig. Power and force rate limitations restrict the feasible range of that actuation force. If the input force distribution of the reference test cannot be replicated in the test rig, the required test rig input force magnitudes may be large or the replication properties poor due to lack of controllability. To circumvent this, a theory of passive components to improve replication and limit the input force demands of dynamic test rigs is developed. The theory fits within the framework of the TWR algorithm.
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26.
  • Johnsson, Roger (författare)
  • Cylinder pressure reconstruction based on complex radial basis function networks from vibration and speed signals
  • 2006
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 20:8, s. 1923-1940
  • Tidskriftsartikel (refereegranskat)abstract
    • Methods to measure and monitor the cylinder pressure in internal combustion engines can contribute to reduced fuel consumption, noise and exhaust emissions. As direct measurements of the cylinder pressure are expensive and not suitable for measurements in vehicles on the road indirect methods which measure cylinder pressure have great potential value. In this paper, a non-linear model based on complex radial basis function (RBF) networks is proposed for the reconstruction of in-cylinder pressure pulse waveforms. Input to the network is the Fourier transforms of both engine structure vibration and crankshaft speed fluctuation. The primary reason for the use of Fourier transforms is that different frequency regions of the signals are used for the reconstruction process. This approach also makes it easier to reduce the amount of information that is used as input to the RBF network. The complex RBF network was applied to measurements from a 6-cylinder ethanol powered diesel engine over a wide range of running conditions. Prediction accuracy was validated by comparing a number of parameters between the measured and predicted cylinder pressure waveform such as maximum pressure, maximum rate of pressure rise and indicated mean effective pressure. The performance of the network was also evaluated for a number of untrained running conditions that differ both in speed and load from the trained ones. The results for the validation set were comparable to the trained conditions.
  •  
27.
  • Josefsson, Andreas, et al. (författare)
  • Spatial location identification of structural nonlinearities from random data
  • 2012
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 27:1, s. 410-418
  • Tidskriftsartikel (refereegranskat)abstract
    • With growing demands on product performance and growing complexity of engineering structures, efficient tools for analyzing their dynamic behavior are essential. Linear techniques are well developed and often utilized. However, sometimes the errors due to linearization are too large to be acceptable, making it necessary to take nonlinear effects into account. In many practical applications it is common and reasonable to assume that the nonlinearities are highly local and thus only affect a limited set of spatial coordinates. The purpose of this paper is to present an approach to finding the spatial location of nonlinearities from measurement data, as this may not always be known beforehand. This information can be used to separate the underlying linear system from the nonlinear parts and create mathematical models for efficient parameter estimation and simulation. The presented approach builds on the reverse-path methodology and utilizes the coherence functions to determine the location of nonlinear elements. A systematic search with Multiple Input/Single Output models is conducted in order to find the nonlinear functions that best describe the nonlinear restoring forces. The obtained results indicate that the presented approach works well for identifying the location of local nonlinearities in structures. It is verified by simulation data from a cantilever beam model with two local nonlinearities and experimental data from a T-beam experimental set-up with a single local nonlinearity. A possible drawback is that a relatively large amount of data is needed. Advantages of the approach are that it only needs a single excitation point that response data at varying force amplitudes is not needed and that no prior information about the underlying linear system is needed.
  •  
28.
  • Khorsand Vakilzadeh, Majid, 1984, et al. (författare)
  • Approximate Bayesian Computation by Subset Simulation using hierarchical state-space models
  • 2017
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 84, s. 2-20
  • Tidskriftsartikel (refereegranskat)abstract
    • A new multi-level Markov Chain Monte Carlo algorithm for Approximate Bayesian Computation, ABC-SubSim, has recently appeared that exploits the Subset Simulation method for efficient rare-event simulation. ABC-SubSim adaptively creates a nested decreasing sequence of data-approximating regions in the output space that correspond to increasingly closer approximations of the observed output vector in this output space. At each level, multiple samples of the model parameter vector are generated by a component-wise Metropolis algorithm so that the predicted output corresponding to each parameter value falls in the current data-approximating region. Theoretically, if continued to the limit, the sequence of data-approximating regions would converge on to the observed output vector and the approximate posterior distributions, which are conditional on the data approximation region, would become exact, but this is not practically feasible. In this paper we study the performance of the ABC-SubSim algorithm for Bayesian updating of the parameters of dynamical systems using a general hierarchical state-space model. We note that the ABC methodology gives an approximate posterior distribution that actually corresponds to an exact posterior where a uniformly distributed combined measurement and modeling error is added. We also note that ABC algorithms have a problem with learning the uncertain error variances in a stochastic state-space model and so we treat them as nuisance parameters and analytically integrate them out of the posterior distribution. In addition, the statistical efficiency of the original ABC-SubSim algorithm is improved by developing a novel strategy to regulate the proposal variance for the component-wise Metropolis algorithm at each level. We demonstrate that Self-regulated ABC-SubSim is well suited for Bayesian system identification by first applying it successfully to model updating of a two degree-of-freedom linear structure for three cases: globally, locally and unidentifiable model classes, and then to model updating of a two degree-of-freedom nonlinear structure with Duffing nonlinearities in its interstory force-deflection relationship. (C) 2016 Elsevier Ltd. All rights reserved.
  •  
29.
  • Khorsand Vakilzadeh, Majid, 1984, et al. (författare)
  • Stochastic finite element model calibration based on frequency responses and bootstrap sampling
  • 2017
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 88, s. 180-198
  • Tidskriftsartikel (refereegranskat)abstract
    • Chemical and topological parameters have been widely used for predicting the phase selection in high-entropy alloys (HEAs). Nevertheless, previous studies could be faulted due to the small number of available data points, the negligence of kinetic effects, and the insensitivity to small compositional changes. Here in this work, 92 TiZrHfM, TiZrHfMM, TiZrHfMMM (M = Fe, Cr, V, Nb, Al, Ag, Cu, Ni) HEAs were prepared by melt spinning, to build a reliable and sufficiently large material database to inspect the robustness of previously established parameters. Modification of atomic radii by considering the change of local electronic environment in alloys, was critically found out to be superior in distinguishing the formation of amorphous and crystalline alloys, when compared to using atomic radii of pure elements in topological parameters. Moreover, crystal structures of alloying element were found to play an important role in the amorphous phase formation, which was then attributed to how alloying hexagonal-close-packed elements and face-centered-cubic or body-centered-cubic elements can affect the mixing enthalpy. Findings from this work not only provide parametric studies for HEAs with new and important perspectives, but also reveal possibly a hidden connection among some important concepts in various fields.
  •  
30.
  • Kiranyaz, Serkan, et al. (författare)
  • 1D convolutional neural networks and applications : A survey
  • 2021
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 151
  • Tidskriftsartikel (refereegranskat)abstract
    • During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. CNNs are feed-forward Artificial Neural Networks (ANNs) with alternating convolutional and subsampling layers. Deep 2D CNNs with many hidden layers and millions of parameters have the ability to learn complex objects and patterns providing that they can be trained on a massive size visual database with ground-truth labels. With a proper training, this unique ability makes them the primary tool for various engineering applications for 2D signals such as images and video frames. Yet, this may not be a viable option in numerous applications over 1D signals especially when the training data is scarce or application specific. To address this issue, 1D CNNs have recently been proposed and immediately achieved the state-of-the-art performance levels in several applications such as personalized biomedical data classification and early diagnosis, structural health monitoring, anomaly detection and identification in power electronics and electrical motor fault detection. Another major advantage is that a real-time and low-cost hardware implementation is feasible due to the simple and compact configuration of 1D CNNs that perform only 1D convolutions (scalar multiplications and additions). This paper presents a comprehensive review of the general architecture and principals of 1D CNNs along with their major engineering applications, especially focused on the recent progress in this field. Their state-of-the-art performance is highlighted concluding with their unique properties. The benchmark datasets and the principal 1D CNN software used in those applications are also publicly shared in a dedicated website. While there has not been a paper on the review of 1D CNNs and its applications in the literature, this paper fulfills this gap. (C) 2020 The Author(s). Published by Elsevier Ltd.
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31.
  • Kiranyaz, Serkan, et al. (författare)
  • Zero-shot motor health monitoring by blind domain transition
  • 2024
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 210
  • Tidskriftsartikel (refereegranskat)abstract
    • Continuous long-term monitoring of motor health is crucial for the early detection of abnormalities such as bearing faults (up to 51% of motor failures are attributed to bearing faults). Despite numerous methodologies proposed for bearing fault detection, most of them require normal (healthy) and abnormal (faulty) data for training. Even with the recent deep learning (DL) methodologies trained on the labeled data from the same machine, the classification accuracy significantly deteriorates when one or few conditions are altered, e.g., a different speed or load, or for different fault types/severities with sensors placed in different locations. Furthermore, their performance suffers significantly or may entirely fail when they are tested on another machine with entirely different healthy and faulty signal patterns. To address this need, in this pilot study, we propose a zero -shot bearing fault detection method that can detect any fault on a new (target) machine regardless of the working conditions, sensor parameters, or fault characteristics. To accomplish this objective, a 1D Operational Generative Adversarial Network (Op-GAN) first characterizes the transition between normal and fault vibration signals of (a) source machine(s) under various conditions, sensor parameters, and fault types. Then for a target machine, the potential faulty signals can be generated, and over its actual healthy and synthesized faulty signals, a compact, and lightweight 1D Self-ONN fault detector can then be trained to detect the real faulty condition in real time whenever it occurs. To validate the proposed approach, a new benchmark dataset is created using two different motors working under different conditions and sensor locations. Experimental results demonstrate that this novel approach can accurately detect any bearing fault achieving an average recall rate of around 89% and 95% on two target machines regardless of its type, severity, and location.
  •  
32.
  • Lagerblad, Ulrika, 1987-, et al. (författare)
  • Dynamic response identification based on state estimation and operational modal analysis
  • 2019
  • Ingår i: Mechanical systems and signal processing. - : Academic Press. - 0888-3270 .- 1096-1216. ; 129, s. 37-53
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents and experimentally validates an augmented Kalman filter extended with a fixed-lag smoother for solving joint state and input estimation problems. Sparse acceleration measurements from a truck side skirt excited by road-induced vibrations from a vibration test track are analysed. The system model is obtained experimentally from an operational modal analysis, reducing modelling errors and avoiding the need for a finite element model and it serves itself as a numerical model. The motion of the truck component is estimated and the results are compared to those of a joint input-state estimation filtering algorithm, in addition to the actual measured motion. Both algorithms are tuned according to a novel process based on minimal a priori information concerning the system states and inputs. The focus of this work is to assess the robustness, performance, and tuning of the algorithms. Two sensor configurations are studied: one where the number of response measurement sensors is high compared to the number of estimated motions and participating modes, and another where the number of response measurements is reduced. Both algorithms perform very well within the first configuration. With a reduced number of response measurements, the fixed-lag smoother is superior to the joint input-state filter in capturing the individual motion of each position on the side skirt.
  •  
33.
  • Li, Guofa, et al. (författare)
  • Detection of road traffic participants using cost-effective arrayed ultrasonic sensors in low-speed traffic situations
  • 2019
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 132, s. 535-545
  • Tidskriftsartikel (refereegranskat)abstract
    • Effective detection of traffic participants is crucial for driver assistance systems. Traffic safety data reveal that the majority of preventable pedestrian fatalities occurred at night. The lack of light at night may cause dysfunction of sensors like cameras. This paper proposes an alternative approach to detect traffic participants using cost-effective arrayed ultrasonic sensors. Candidate features were extracted from the collected episodes of pedestrians, cyclists, and vehicles. A conditional likelihood maximization method based on mutual information was employed to select an optimized subset of features from the candidates. The belonging probability to each group along with time was determined based on the accumulated object type attributes outputted from a support vector machine classifier at each time step. Results showed an overall detection accuracy of 86%, with correct detection rate of pedestrians, cyclists and vehicles around 85.7%, 76.7% and 93.1%, respectively. The time needed for detection was about 0.8 s which could be further shortened when the distance between objects and sensors was shorter. The effectiveness of arrayed ultrasonic sensors on objects detection would provide all-around-the-clock assistance in low-speed situations for driving safety.
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34.
  • Li, Hailong, 1976-, et al. (författare)
  • A self-powered smart wave energy converter for sustainable sea
  • 2024
  • Ingår i: Mechanical systems and signal processing. - : Academic Press. - 0888-3270 .- 1096-1216. ; 220
  • Tidskriftsartikel (refereegranskat)abstract
    • Self-powered smart buoys are widely used in sustainable sea, such as marine environmental monitoring. The article designs a self-powered and self-sensing point-absorber wave energy converter based on the two-arm mechanism. The system consists of the wave energy capture module, the power take-off module, the generator module and the energy storage module. As the core component of the wave energy converter, the power take-off module is mainly composed of a two-arm mechanism, which can convert the oscillation heave motion into unidirectional rotary motion. To evaluate the power generation performance of the system, the kinematic and dynamic models of the wave energy converter with the flywheel are established, and the disengagement and engagement phenomena of the flywheel are analyzed. The effectiveness of the prototype in capturing wave energy is verified through dry experiments in lab and field tests. The dry experiment reveals that the maximum output power of the system is 5.67 W, and the maximum and average mechanical efficiency are 66.63 % and 48.35 %, respectively. Additionally, the field test demonstrates that the peak output power can reach 92 W. Meanwhile, the generated electrical signals can be processed by deep learning algorithms to accurately identify different wave states. This high performance confirms that the proposed wave energy converter can meet its own energy needs by capturing wave energy in the marine environment, while also achieving self-sensing for wave condition monitoring. The system has great potential for promoting the development of intelligent sustainable sea in the future. 
  •  
35.
  • Linderholt, Andreas, 1968-, et al. (författare)
  • Optimizing the informativeness of test data used for computational model updating
  • 2005
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 19:4, s. 736-750
  • Tidskriftsartikel (refereegranskat)abstract
    • In advance of a computational model updating or an error localisation, it can be advantageous to make a preparatory error localisation using data from a nominal analytical model. The purpose is then to select parameters for quantifying model errors and also to design effective tests for determining the best parameter setting. For successful subsequent error localisation, the test data must be informative with respect to the model parameters chosen when such data become available after test. The demand for test data informativeness puts requirements on the experiment with regard to spatial resolution of sensors, bandwidth of excitation, signal-to-noise ratios, etc.Optimising a test design is a huge task, sometimes impossible in practice, due to its combinatorial nature. The number of possible sensor/actuator placement combinations grows rapidly as the number of sensor and actuator candidates increases. For industrial sized problems, finding a sub-optimal solution may be a more realistic target. Such solutions are sought in this work.The aim of this study is to quantify data informativeness, shown to relate to the Fisher information matrix, with respect to physical parameters that are used in error localisation and model updating. Deterministic finite-element models in combination with stochastic noise models are used for assessing data informativeness, and a procedure for test design optimisation with respect to this is devised.
  •  
36.
  • Linderholt, Andreas, 1968-, et al. (författare)
  • Parameter Identifiability in Finite Element Model Error Localization
  • 2003
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 17:3, s. 579-588
  • Tidskriftsartikel (refereegranskat)abstract
    • A fundamental question in finite element model updating and error localisation is whether sufficient identifiability of model parameters is at hand for a given set of test data. Under certain conditions, the dynamic properties (to be compared with test data) of a structural model, may change similarly when a certain model parameter or a combination of other parameters are modified. Since low confidence in identified parameters can also be expected for marginally identifiable systems, due to the omnipresent noise when real test data are used, one should seek such states so as to avoid them. Should the problem lack identifiability, then before a meaningful error localisation can be made; either complementary test data have to be added or new parameters chosen for the model. The latter is studied in this paper. An index, the orthogonality/colinearity index, was developed to facilitate finding the best way to reduce the number of parameters when there is low identifiability The use of the index is demonstrated on a six-degree-of-freedom system in a numerical example. The example shows that error localisation or model updating using a parameterisation which has insufficient parameter identifiability is pointless.
  •  
37.
  • Lindgren, Georg, et al. (författare)
  • Transfer-function approximations of the rainflow filter
  • 2002
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 1096-1216 .- 0888-3270. ; 16:6, s. 979-989
  • Tidskriftsartikel (refereegranskat)abstract
    • The rainflow filter is a non-linear filter which can be used to eliminate small-amplitude oscillations in a signal. In this paper, two approaches for investigation of the filter by means of an approximating transfer function are presented. The estimates are obtained from rainflow-filtered spectral simulations. One method is based on clipped Gaussian processes, the other uses a spline interpolation in the filtered time series. Examples are given for processes with different types of spectral densities. A certain reduction of small-amplitude cycles is obtained by use of the transfer function, but the threshold effect, characteristic for the rainflow filter, is missed.
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38.
  • Liu, Zibo, 1989-, et al. (författare)
  • Locally resonant metamaterial curved double wall to improve sound insulation at the ring frequency and mass-spring-mass resonance
  • 2021
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 149
  • Tidskriftsartikel (refereegranskat)abstract
    • A locally resonant metamaterial curved double wall is proposed and studied. The aim is to improve the sound insulation by introducing a metamaterial design targeting a narrow fre-quency band region associated with characteristic frequencies of curved double walls, thus enabling an overall improvement of sound insulation properties in a broader frequency range. This metamaterial is realized by introducing periodically distributed resonators to a curved double wall. The sound transmission loss properties of such curved double walls are first investigated by using the concept of 'apparent impedance', which expresses the properties of the whole structure in terms of the impedances of the constituting panels and air cavity. The apparent impedance approach is validated against Finite Element models. It is shown that, instead of a dip in the sound transmission loss around the ring fre-quency of a single curved panel, the curved double wall may exhibit a broad 'valley' with low sound transmission loss, whose bandwidth is determined by the spacing between the two characteristic frequencies of the structure (associated with the ring frequency and mass-spring-mass resonance of the curved double wall). The curved double wall is then specifically designed by adjusting the two characteristic frequencies to be close to each other in order to narrow the region associated with a low transmission loss. This enables, subsequently, to improve the transmission loss in this region by effectively inserting tuned local resonators. The design principles are discussed, and applications of double walls consisting either of the same curved panels or different curved panels are both included.
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39.
  • Lopez Arteaga, Ines, et al. (författare)
  • Improved source reconstruction in Fourier-based Near-field Acoustic Holography applied to small apertures
  • 2012
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 32, s. 359-373
  • Tidskriftsartikel (refereegranskat)abstract
    • It is well known that Fourier-based Near-field Acoustic Holography fails to produce good source reconstructions when the aperture size of the microphone array is smaller than the source size. In this paper this problem is overcome by pre-conditioning the spatial hologram data using Linear Predictive Border Padding (LPBP) before it is Fourier-transformed to the wave-number domain. It is shown that LPBP allows for very small aperture sizes with a good reconstruction accuracy. An exhaustive analysis of LPBP is presented based on numerical experiments and measured data. The numerical experiments are performed on two different source types: modal patterns and point sources. These two types of sources represent the two limit situations that one can find in practice: modal patterns have a tonal spectrum in the spatial wave-number domain and are relatively easy to reconstruct accurately, while point sources have a broad-band wave-number spectrum which makes them very challenging to reconstruct. In order to illustrate the accuracy of the method in practice, results of measurements on a hard disk drive are presented as well. For a given distance to the source, the position and size of the hologram plane apertures is varied and the reconstructed source information is compared to the original source data. The reconstructed sources are compared both qualitatively and quantitatively. The results show that LPBP is an efficient and accurate extrapolation method, which leads to accurate reconstructions even for very small aperture sizes.
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40.
  • Maes, K., et al. (författare)
  • Tracking of inputs, states and parameters of linear structural dynamic systems
  • 2019
  • Ingår i: Mechanical systems and signal processing. - : ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD. - 0888-3270 .- 1096-1216. ; 130, s. 755-775
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents a novel algorithm for joint input-state-parameter estimation in structural dynamics. The algorithm is derived from an existing smoothing algorithm. In each time step, the system model adopted in the joint input-state-parameter estimation is linearized around the current state, yielding an algorithm similar to the extended Kalman filter. It is shown that adopting a time delay in the estimation can significantly reduce the estimation error, especially in case data originates from sensors that are not collocated with the estimated inputs. Analytical expressions for the sensitivities of the system matrices with respect to unknown parameters are derived for the case of a linear underlying state-space model. These sensitivities are derived for models expressed in physical coordinates, models expressed in modal coordinates, and modally reduced-order models with a quasi-static correction to account for the contribution of the out-of-band modes. The proposed methodology is verified using numerical simulations and validated using data obtained from a laboratory experiment on a steel beam with I-shaped cross section.
  •  
41.
  • Mahata, Kaushik, et al. (författare)
  • On the estimation of complex modulus and Poisson's ratio using longitudinal wave experiments
  • 2006
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 20:8, s. 2080-2094
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper we consider different least-squares-based approaches for estimating the complex Young's modulus and the complex Poisson's ratio of a viscoelastic material using a longitudinal wave propagation experiment. We present a statistical analysis of different estimation approaches and compare their performances. The analytical covariance expressions are validated using experimental data.
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42.
  • Mattsson, Per, et al. (författare)
  • Identification of cascade water tanks using a PWARX model.
  • 2018
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 106, s. 40-48
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper we consider the identification of a discrete-time nonlinear dynamical model for a cascade water tank process. The proposed method starts with a nominal linear dynamical model of the system, and proceeds to model its prediction errors using a model that is piecewise affine in the data. As data is observed, the nominal model is refined into a piecewise ARX model which can capture a wide range of nonlinearities, such as the saturation in the cascade tanks. The proposed method uses a likelihood-based methodology which adaptively penalizes model complexity and directly leads to a computationally efficient implementation.
  •  
43.
  • Milosevic, Marko, 1991, et al. (författare)
  • Reconstruction of sleeper displacements from measured accelerations for model-based condition monitoring of railway crossing panels
  • 2023
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 192
  • Tidskriftsartikel (refereegranskat)abstract
    • Railway switches and crossings (S&C, turnouts) connect different track sections and create a railway network by allowing trains to change tracks. This functionality comes at a cost as the load-inducing rail discontinuities in the switch and crossing panels cause much larger degradation rates for S&C compared to regular plain line tracks. The high degradation rates make remote condition monitoring an interesting prospect for infrastructure managers to optimise maintenance and ensure safe operations. To this end, this paper addresses the development of tailored signal processing tools for condition monitoring using embedded accelerometers in crossing panels. Multibody simulations of the dynamic train–track interaction are used to aid the interpretation of the measured signals in a first step towards building a model-based condition monitoring system. An analysis is performed using sleeper acceleration measurement data generated by 100 000 train passages in eight crossing panels. Based on the given data, a novel frequency-domain displacement reconstruction method is developed and the robustness of the method with respect to encountered operational variability of the measured data is demonstrated. The separation of the track response into quasi-static and dynamic domains based on deformation wavelength regions is proposed as a promising strategy to observe the ballast condition and the crossing geometry condition, respectively.
  •  
44.
  • Mishra, Madhav, et al. (författare)
  • Particle filter-based prognostic approach for railway track geometry
  • 2017
  • Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 96, s. 226-238
  • Tidskriftsartikel (refereegranskat)abstract
    • Track degradation of ballasted railway track systems has to be measured on a regular basis, and these tracks must be maintained by tamping. Tamping aims to restore the geometry to its original shape to ensure an efficient, comfortable and safe transportation system. To minimize the disturbance introduced by tamping, this action has to be planned in advance. Track degradation forecasts derived from regression methods are used to predict when the standard deviation of a specific track section will exceed a predefined maintenance or safety limit. This paper proposes a particle filter-based prognostic approach for railway track degradation; this approach is demonstrated by examining different railway switches. The standard deviation of the longitudinal track degradation is studied, and forecasts of the maintenance limit intersection are derived. The particle filter-based prognostic results are compared with the standard regression method results for four railway switches, and the particle filter method shows similar or better result for the four cases. For longer prediction times, the error of the proposed method is equal to or smaller than that of the regression method. The main advantage of the particle filter-based prognostic approach is its ability to generate a probabilistic result based on input parameters with uncertainties. The distributions of the input parameters propagate through the filter, and the remaining useful life is presented using a particle distribution.
  •  
45.
  • Mohammed, Omar D., et al. (författare)
  • Dynamic modelling of a one-stage spur gear system and vibration-based tooth crack detection analysis
  • 2015
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 54:1, s. 293-305
  • Tidskriftsartikel (refereegranskat)abstract
    • For the purpose of simulation and vibration-based condition monitoring of a geared system, it is important to model the system with an appropriate number of degrees of freedom (DOF). In earlier papers several models were suggested and it is therefore of interest to evaluate their limitations. In the present study a 12 DOF gear dynamic model including a gyroscopic effect was developed and the equations of motions were derived. A one-stage reduction gear was modelled using three different dynamic models (with 6, 8 and 8 reduced to 6 DOF), as well as thedeveloped model (with 12 DOF), which is referred as the fourth model in this paper. The time-varying mesh stiffness was calculated, and dynamic simulation was then performed for different crack sizes. Time domain scalar indicators (the RMS, kurtosis and the crest factor) were applied for fault detection analysis. The results of the first model showa clearly visible difference from those of the other studied models, which were made more realistic by including two more DOF to describe the motor and load. Both the symmetric and the asymmetric disc cases were studied using the fourth model. In the case of disc symmetry, the results of the obtained response are close to those obtained from both the second and third models. Furthermore, the second model showed a slight influence from inter-tooth friction, andtherefore the third model is adequate for simulating the pinion’s y-displacement in the case of the symmetric disc. In the case of the asymmetric disc, the results deviate from those obtained in the symmetric case. Therefore, for simulating the pinion’s y-displacement, the fourth model can be considered for more accurate modelling in the case of the asymmetric disc.
  •  
46.
  • Mohammed, Omar D., et al. (författare)
  • Dynamic Response and Time-Frequency Analysis for Gear Tooth Crack Detection
  • 2016
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 66-67, s. 612-624
  • Tidskriftsartikel (refereegranskat)abstract
    • Vibration health monitoring is a non-destructive technique which can be applied to detect cracks propagating in gear teeth. This paper studies gear tooth crack detection by investigating the natural frequencies and by performing time-frequency analysis of a 6 DOF dynamic gear model. The gear mesh stiffness used in the model was calculated analytically for different cases of crack sizes. The frequency response functions (FRFs) of the model were derived for healthy and faulty cases and dynamic simulation was performed to obtain the time signal responses. A new approach involving a short-time Fourier transform (STFT) was applied where a fast Fourier transform (FFT) was calculated for successive blocks with different sizes corresponding to the time segments of the varying gear mesh stiffness. The relationship between the different crack sizes and the mesh-stiffness-dependent eigenfrequencies was studied in order to detect the tooth crack and to estimate its size.
  •  
47.
  • Mohammed, Omar D., et al. (författare)
  • Vibration signal analysis for gear fault diagnosis with various crack progression scenarios
  • 2013
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 41:1-2, s. 176-195
  • Tidskriftsartikel (refereegranskat)abstract
    • There are different analytical scenarios assumed for crack propagation in the gear tooth root. This paper presents an investigation of the performance of statistical fault detection indicators (the RMS and kurtosis) for three different series of crack propagation scenarios, to compare these scenarios from a fault diagnostics point of view. These scenarios imply different forms of cracks with propagation by a certain step of crack depth. The 1st scenario assumes a crack being extended through the whole tooth width with a uniform crack depth distribution, while the 2nd scenario assumes the crack being extended through the whole tooth width with a parabolic crack depth distribution, and finally in the 3rd scenario the crack is assumed to be propagating in both the depth and the length directions simultaneously. The time-varying gear mesh stiffness has been investigated using the program code developed in the present research, and the crack propagation can be modelled with any of the presented crack propagation scenarios. Dynamic simulation has been performed to obtain the residual signals of all the studied cases for each crack propagation scenario. The comparison of the statistical indicators applied to the residual signals shows that in the 1st scenario the faults are most easily detectable, since in this scenario there is a change in the indicators implying a dramatic decrease in the gear mesh stiffness. The fault detection in the 2nd scenario is more difficult, as the crack propagates with no significant reflection on the mesh stiffness loss. The 3rd proposed scenario should receive more attention in research because it could occur in reality in case of non-uniform load distribution. However, with this scenario it is difficult to perform early fault detection, since there is a very slight change in the statistical indicators at the beginning of the crack propagation. After which, these indicators show a significant change when the crack grows deeper which implies a serious crack propagation condition.
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48.
  •  
49.
  • Norlander, Hans, et al. (författare)
  • Parameter estimation from wave propagation tests on a tube perforated by helical slots
  • 2013
  • Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 40:1, s. 385-399
  • Tidskriftsartikel (refereegranskat)abstract
    • For a tube with doubly symmetric cross section and perforations by helical slots there is a coupling between extension and torsion. In this paper a one dimensional (1D) model structure for a tube with such a helical slot segment (HSS) is established, and parameters accounting for the coupling between extension and torsion are estimated from wave propagation experiments. In these experiments incident extensional waves were generated through axial impact by strikers of different lengths, causing reflected and transmitted waves of extensional and torsional type which were measured in terms of surface strains on either side of the HSS part of the tube. A statistical test on the experimental data shows that the output residuals (the difference between modeled and experimental output) cannot be explained by measurement noise alone. This is not surprising since the 1D model structure is based on some simplifying assumptions concerning the geometry of the HSS. Parameters for two different geometries of the HSS are estimated, and the models are assessed in terms of model fa, simulations and wave energy distribution. It turns out that for one case, where the geometrical assumptions are valid, the 1D model is adequate, while for another case, where the validity of the assumptions is questionable, it is not. It is concluded that the 1D model structure provides a simple and efficient description of the HSS if the geometrical assumptions are valid.
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50.
  • Rahrovani, Sadegh, 1981, et al. (författare)
  • Modal Dominancy Analysis Based on Modal Contribution to Frequency Response Function ℋ2-Norm
  • 2014
  • Ingår i: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 48:1-2, s. 218-231
  • Tidskriftsartikel (refereegranskat)abstract
    • A main restriction in the general applicability of modal reduction techniques has been the lack of a proper dominancy analysis as well as the lack of a guaranteed bound for the approximation error. In this study, a modal dominancy approach for reduction of dynamical systems is presented. A quadratic-metric, introduced based on modal contribution to the ℋ2ℋ2-norm of the frequency response function matrix, is given in closed-form formulation. Briefly stated, a performance and error analysis of the proposed modal dominancy procedure is carried out, the problem of metric non-uniqueness as well as the treatment of structural non-minimality for a class of systems with multiple eigenvalues is described, and a method to circumvent this problem is proposed. In treating problems with high-dimensional input space, such as in moving and/or distributed loading problems, the presented method is an improvement as it incorporates information extracted from the structural and spectral properties of the input force in the modal dominancy analysis. In addition, the method׳s performance is validated for reduction of a large-scale finite element model, originated from a moving load problem in railway mechanics, and the results are compared with the balancing approach.
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