| 1. |
- Adin, Veysi, et al.
(författare)
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Tiny Machine Learning for Damage Classification in Concrete Using Acoustic Emission Signals
- 2023
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Ingår i: 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). - : IEEE. - 9781665453837
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Konferensbidrag (refereegranskat)abstract
- Acoustic emission (AE) is a widely used non-destructive test method in structural health monitoring applications to identify the damage type in the material. Usually, the analysis of the AE signal is done by using traditional parameter-based methods. Recently, machine learning methods showed promising results for the analysis of AE signals. However, these machine learning models are complex, slow, and consume significant amounts of energy. To address these limitations and to explore the trade-off between model complexity and the classification accuracy, this paper presents a lightweight artificial neural network model to classify damage types in concrete material using raw acoustic emission signals. The model consists of one hidden layer with four neurons and is trained on a public acoustic emission signal dataset. The created model is deployed to several microcontrollers and the performance of the model is evaluated and compared with a state-of-the-art machine learning model. The model achieves 98.4% accuracy on the test data with only 4019 parameters. In terms of evaluation metrics, the proposed tiny machine learning model outperforms previously proposed models 10 to 1000 times. The proposed model thus enables machine learning in real-time structural health monitoring applications.
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| 2. |
- Adin, Veysi, et al.
(författare)
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Tiny Machine Learning for Real-Time Postural Stability Analysis
- 2023
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Ingår i: 2023 IEEE Sensors Applications Symposium (SAS). - : IEEE conference proceedings. - 9798350323078
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Konferensbidrag (refereegranskat)abstract
- Postural sway is a critical measure for evaluating postural control, and its analysis plays a vital role in preventing falls among the elderly. Typically, physiotherapists assess an individual's postural control using tests such as the Berg Balance Scale, Tinetti Test, and time up-and-go test. Sensor-based analysis is available based on devices such as force plates or inertial measurement units. Recently, machine learning methods have demonstrated promising results in the sensor-based analysis of postural control. However, these models are often complex, slow, and energy-intensive. To address these limitations, this study explores the design space of lightweight machine learning models deployable to microcontrollers to assess postural stability. We developed an artificial neural network (ANN) model and compare its performance to that of random forests, gaussian naive bayes, and extra tree classifiers. The models are trained using a sway dataset with varying input sizes and signal-to-noise ratios. The dataset comprises two feature vectors extracted from raw accelerometer data. The developed models are deployed to an ARM Cortex M4-based microcontroller, and their performance is evaluated and compared. We show that the ANN model has 99.03% accuracy, higher noise immunity, and the model performs better with a window size of one second with 590.96 us inference time.
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| 3. |
- Aranda, Jesus Javier Lechuga, et al.
(författare)
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A space-coiling resonator for improved energy harvesting in fluid power systems
- 2019
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Ingår i: Sensors and Actuators A-Physical. - Elsevier : Elsevier. - 0924-4247 .- 1873-3069. ; 291, s. 58-67
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Tidskriftsartikel (refereegranskat)abstract
- Pressure fluctuation energy harvesting devices are promising alternatives to power up wireless sensors in fluid power systems. In past studies, classical Helmholtz resonators have been used to enhance the energy harvesting capabilities of these harvesters. Nevertheless, for fluctuations with frequency components in the range of less than 1000 Hz, the design of compact resonators is difficult, mostly for their poor acoustic gain. This paper introduces a space-coiling resonator fabricated using 3D printing techniques. The proposed resonator can achieve a better acoustic gain bounded by a small bulk volume compared to a classic Helmholtz resonator, improving the energy harvesting capabilities of pressure fluctuation energy harvesters. The resonator is designed and evaluated using finite-element-method techniques and examined experimentally. Three space-coiling-resonators are designed, manufactured and compared to classic Helmholtz resonators for three frequencies: 280 Hz, 480 Hz and 920 Hz. This work displays the possibility of compact, high-performance pressure fluctuation energy harvesters and the advantages of the space-coiling printed resonators to enhance the harvesting performance.
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| 4. |
- Aranda, Jesus Javier Lechuga, et al.
(författare)
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An Apparatus For The Performance Estimation Of Pressure Fluctuation Energy Harvesters
- 2018
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - : IEEE. - 0018-9456 .- 1557-9662. ; 67:11, s. 2705-2713
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Tidskriftsartikel (refereegranskat)abstract
- Hydraulic pressure fluctuation energy harvesters are promising alternatives to power up wireless sensor nodes in hydraulic systems. The characterization of these harvesters under dynamic and band-limited pressure signals is imperative for the research and development of novel concepts. To generate and control these signals in a hydraulic medium, a versatile apparatus capable of reproducing pressure signals is proposed. In this paper, a comprehensive discussion of the design considerations for this apparatus and its performance is given. The suggested setup enables the investigation of devices tailored for the harvesting of energy in conventional hydraulic systems. To mimic these systems, static pressures can be tuned up to 300 bar, and the pressure amplitudes with a maximum of 28 Bar at 40 Hz and 0.5 bar at 1000 Hz can be generated. In addition, pressure signals found in commercial hydraulic systems can be reproduced with good accuracy. This apparatus proves to be an accessible, robust, and versatile experimental setup to create environments for the complete performance estimation of pressure fluctuation energy harvesters.
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| 5. |
- Aranda, Jesus Javier Lechuga, et al.
(författare)
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Fluid coupling interfaces for hydraulic pressure energy harvesters
- 2017
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Ingår i: 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). - : IEEE. - 9781509059980 ; , s. 1556-1562
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Konferensbidrag (refereegranskat)abstract
- The need for wireless sensor networks that can run for long times without the need of battery replacement has risen the need for energy harvesters. Industrial environments have plenty of energy sources that can be harvested; pressure fluctuations are a high energy density source that can be harvested using piezoelectric devices. Present devices have introduced flat metallic plates as the main force transmission elements for hydraulic fluctuations energy harvesters. In this paper, we analyze the force transmission efficiency of flat plates when used as the primary fluid coupling interface in hydraulic energy harvesters. Previous work has been focused on the optimization of circuit matching and pressure ripple amplification. In this work, we offer a look into the efficiencies of flat plates in different configurations and pressure loads. The analysis shows that despite the reasonable force transmission efficiency of flat plates in low-pressure environments, the overall efficiency of hydraulic energy harvesters can be improved if instead of flat plates, conventional hydraulic actuators, such as piston cylinders, could be used.
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| 6. |
- Aranda, Jesus Javier Lechuga, et al.
(författare)
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Force Transmission Interfaces for Pressure Fluctuation Energy Harvesters
- 2018
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Ingår i: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. - : IEEE. - 9781509066841 ; , s. 4230-4235
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Konferensbidrag (refereegranskat)abstract
- Wireless sensor nodes in state of the art fluid power systems used in monitoring and maintenance prediction demand long lasting power sources that do not rely on batteries. Energy harvesting is a promising technology that can provide the required energy to power wireless sensors. Pressure fluctuation energy harvesters can be employed in conventional hydraulic systems to convert the acoustic pressure fluctuation to electrical power. Present studies have explored the overall efficiency of these devices while experimentally describing losses in piezoelectric and circuit interfaces, nevertheless there is no study on the fluid to mechanical force transmission efficiency. In this paper we investigate the pressure to force transmission rate of two types of fluid to mechanical interfaces: a flat metal plate and a conventional hydraulic piston. The interfaces are investigated in conditions similar to those found in conventional hydraulic systems. The study shows that flat plate exhibit good force transmission for low pressure applications with a constant rate across frequencies, while exhibiting a decrease in force transmission at higher pressures. On the other hand the piston exhibit a more robust pressure design, with a constant force transmission rate at all pressures but with a dampening of force at higher frequencies. It is shown that small differences in force transmission ratios can have a considerable impact on the power generation.
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| 7. |
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| 8. |
- Aranda, Jesus Javier Lechuga
(författare)
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Towards Self-Powered Devices Via Pressure Fluctuation Energy Harvesters
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The growing interest in the Internet of Things has created a need for wireless sensing systems for industrial and consumer applications. In hydraulic systems, a widely used method of power transmission in industry, wireless condition monitoring can lead to reduced maintenance costs and increase the capacity for sensor deployment. A major problem with the adoption of wireless sensors is the battery dependence of current technologies. Energy harvesting from pressure fluctuations in hydraulic systems can serve as an alternative power supply and enable self-powered devices. Energy harvesting from pressure fluctuations is the process of converting small pressure fluctuations in hydraulic fluid into a regulated energy supply to power low power electronics. Previous studies have shown the feasibility of pressure fluctuation harvesting. However, for the development of self-powered sensor systems, the methods and techniques for converting pressure fluctuations into electrical energy should be further investigated.This thesis explores the methods, limitations, opportunities and trade-offs involved in the development of pressure fluctuation energy harvesters in the context of self-powered wireless devices. The focus is on exploring and characterizing the various mechanisms required to convert pressure fluctuations into electrical energy. In this work, an energy harvesting device consisting of a fluid-to-mechanical interface, an acoustic resonator, a piezoelectric stack, and an interface circuit is proposed and evaluated. Simulations and experimental analysis were used to analyse these different components for excitation relevant to hydraulic motors.The results of this work provide new insights into the development of power supplies for self-powered sensors for hydraulic systems using pressure fluctuation energy harvesters. It is shown that with the introduction of the space coiling resonator for pressure fluctuation amplification and a detailed analysis of the fluid interface and power conditioning circuits, the understanding of the design and optimization of efficient pressure fluctuation energy harvesters is further advanced.
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| 9. |
- Aranda, Jesus Javier, et al.
(författare)
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Self-powered wireless sensor using a pressure fluctuation energy harvester
- 2021
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:4
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Tidskriftsartikel (refereegranskat)abstract
- Condition monitoring devices in hydraulic systems that use batteries or require wired infrastructure have drawbacks that affect their installation, maintenance costs, and deployment flexibility. Energy harvesting technologies can serve as an alternative power supply for system loads, eliminating batteries and wiring requirements. Despite the interest in pressure fluctuation energy harvesters, few studies consider end-to-end implementations, especially for cases with lowamplitude pressure fluctuations. This generates a research gap regarding the practical amount of energy available to the load under these conditions, as well as interface circuit requirements and techniques for efficient energy conversion. In this paper, we present a self-powered sensor that integrates an energy harvester and a wireless sensing system. The energy harvester converts pressure fluctuations in hydraulic systems into electrical energy using an acoustic resonator, a piezoelectric stack, and an interface circuit. The prototype wireless sensor consists of an industrial pressure sensor and a low-power Bluetooth System-on-chip that samples and wirelessly transmits pressure data. We present a subsystem analysis and a full system implementation that considers hydraulic systems with pressure fluctuation amplitudes of less than 1 bar and frequencies of less than 300 Hz. The study examines the frequency response of the energy harvester, the performance of the interface circuit, and the advantages of using an active power improvement unit adapted for piezoelectric stacks. We show that the interface circuit used improves the performance of the energy harvester compared to previous similar studies, showing more power generation compared to the standard interface. Experimental measurements show that the self-powered sensor system can start up by harvesting energy from pressure fluctuations with amplitudes starting at 0.2 bar at 200 Hz. It can also sample and transmit sensor data at a rate of 100 Hz at 0.7 bar at 200 Hz. The system is implemented with off-the-shelf circuits.
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| 10. |
- Bader, Sebastian, 1984-, et al.
(författare)
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A Comparison of One- and Two-Diode Model Parameters at Indoor Illumination Levels
- 2020
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Ingår i: IEEE Access. - 2169-3536. ; 8, s. 172057-172064
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Tidskriftsartikel (refereegranskat)abstract
- Indoor photovoltaic (PV) application gains in attraction for low-power electronic systems, which requires accurate methods for performance predictions in indoor environments. Despite this, the knowledge on the performance of commonly used photovoltaic device models and their parameter estimation techniques in these scenarios is very limited. Accurate models are an essential tool for conducting feasibility analyses and component dimensioning for indoor photovoltaic systems. In this paper, we therefore conduct a comparison of the one- and two-diode models with parameters estimated based on two well-known methods. We evaluate the models' performance on datasets of photovoltaic panels intended for indoor use, and illumination conditions to be expected in indoor environments lit by artificial light sources. The results demonstrate that the one-diode model outperforms the two-diode model with respect to the estimation of the overall I-V characteristics. The two-diode model results instead in lower maximum power point errors. Both models show a sensitivity to initial conditions, such as the selection of the diode ideality factor, as well as the curve form of the photovoltaic panel to be modeled, which has not been acknowledged in previous research.
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