| 1. |
|
|
| 2. |
- Baumann, N., et al.
(författare)
-
Piepser 2.0 : A Self-Sustaining Smartwatch to Maximize the Paragliders Flytime
- 2020
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - : Institute of Electrical and Electronics Engineers Inc.. - 0018-9456 .- 1557-9662. ; 69:4, s. 1445-1454
-
Tidskriftsartikel (refereegranskat)abstract
- The main motivation of paraglider pilots is to stay in the air for as long as possible. Therefore, paraglider pilots are always searching for thermal upwind that allow them to gain altitude. These thermal lifts are difficult to detect. Therefore, sensors and devices that indicate the vertical speed (so-called variometers) are widely used among paraglider pilots. This article presents the design and the implementation of an ultralow-power, self-sustaining, high-precision, wrist-worn variometer with a minimal form factor but infinite lifetime, which can visually and acoustically indicate the vertical velocity. This article demonstrates the benefits of combining multisource energy harvesting (EH) for wearable devices with low power design, exploiting a novel near-threshold ARM Cortex-M4F microcontroller, the Ambiq Apollo2, for the onboard processing. The experimental results show a power consumption of only 17.12~\mu \text{W} in sleep mode and 1937.21~\mu \text{W} in the worst case scenario when processing the data and outputting an audio feedback. Measurements confirmed that combining both thermal and solar EH makes the designed electronics self-sustaining. Without EH, the system will be operational for up to 372 h in always-on mode (worst case scenario) supplied by a 200-mAh lithium-ion battery. © 1963-2012 IEEE.
|
|
| 3. |
- Beltramelli, Luca, et al.
(författare)
-
Energy efficiency of slotted LoRaWANcommunication with out-of-band synchronization
- 2021
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - 0018-9456 .- 1557-9662.
-
Tidskriftsartikel (refereegranskat)abstract
- Although the idea of using wireless links for covering large areas is not new, the advent of Low Power Wide area networks (LPWANs) has recently started changing the game. Simple, robust, narrowband modulation schemes permit the implementation of low-cost radio devices offering high receiver sensitivity, thus improving the overall link budget. The several technologies belonging to the LPWAN family, including the well-known LoRaWAN solution, provide a cost-effective answer to many Internet-of-things (IoT) applications, requiring wireless communication capable of supporting large networks of many devices (e.g., smart metering). Generally, the adopted medium access control (MAC) strategy is based on pure ALOHA, which, among other things, allows to minimize the traffic overhead under constrained duty cycle limitations of the unlicensed bands. Unfortunately, ALOHA suffers from poor scalability, rapidly collapsing in dense networks. This work investigates the design of an improved LoRaWAN MAC scheme based on slotted ALOHA. In particular, the required time dissemination is provided by out-of-band communications leveraging on Radio Data System(FM-RDS) broadcasting, which natively covers wide areas both indoor and outdoor. An experimental setup based on low-cost hardware is used to characterize the obtainable synchronization performance and derive a timing error model. Consequently, improvements in success probability and energy efficiency have been validated by means of simulations in very large networks with up to 10000 nodes. It is shown that the advantage of the proposed scheme over conventional LoRaWAN communication is up to 100% when short update time and large payload are required. Similar results are obtained regarding the energy efficiency improvement, that is close to 100% for relatively short transmission intervals and long message duration; however, due to the additional overhead for listening the time dissemination messages, efficiency gain can be negative for very short duration of message fastly repeating.
|
|
| 4. |
- Capriglione, D., et al.
(författare)
-
Experimental Analysis of Filtering Algorithms for IMU-Based Applications under Vibrations
- 2021
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - : Institute of Electrical and Electronics Engineers Inc.. - 0018-9456 .- 1557-9662. ; 70
-
Tidskriftsartikel (refereegranskat)abstract
- The use of microelectro-mechanical systems (MEMS)-based inertial measurement units (IMUs) is widespread in many applications concerning monitoring, diagnostic, and/or controlling in navigation and transportation systems, as well as in low-cost applications for automotive and aeronautical fields. The data provided by the set of sensors typically present in IMUs, as accelerometers, gyroscopes, and magnetometers, are often used also for feeding suitable filtering and positioning algorithms able to correct the attitude and path of the vehicle on which they are installed or to provide the analytical redundancy needed for online diagnosis. Nevertheless, on one hand, the performance of low-cost MEMS-based IMUs is certified only under a small set of nominal operating conditions, and on the other hand, the filtering algorithms are often designed and verified under canonical additive noises. In this framework, this article proposes a test plan and a test setup for analyzing and characterizing the performance of filtering algorithms for positioning based on data coming from low-cost IMUs and able to verify systematically the operation of such algorithms under real scenarios. Two kinds of very popular filtering algorithms have been considered, namely, the complementary filter and the attitude and heading reference systems (AHRS) Kalman filter, which belong to two opposite approaches. The experimental results prove how the typical vibrations present in real scenarios can significantly affect the performance of such algorithms. © 1963-2012 IEEE.
|
|
| 5. |
- Capriglione, D., et al.
(författare)
-
Soft Sensors for Instrument Fault Accommodation in Semiactive Motorcycle Suspension Systems
- 2020
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - : Institute of Electrical and Electronics Engineers Inc.. - 0018-9456 .- 1557-9662. ; 69:5, s. 2367-2376
-
Tidskriftsartikel (refereegranskat)abstract
- This article describes the development and experimental verification of an instrument fault accommodation (IFA) scheme for front and rear suspension stroke sensors in motorcycles equipped with electronically controlled semiactive suspension systems. In particular, the IFA scheme is based on the use of nonlinear autoregressive with exogenous inputs (NARX) neural networks (NNs) employed as soft sensors for feeding the suspension control strategy back with measurement even in the presence of faults occurred on the sensors. Different NN architectures have been trained and tuned by considering real data acquired during several measurement campaigns. The performance has been compared with that of the well-known half-car model (HCM). Very satisfying results allow the soft sensor to be really integrated into fault-tolerant control systems. In experimental road tests, an implementation of the proposed IFA scheme on a low-cost microcontroller for automotive applications showed to be in real time. In this article, these experimental results are shown to prove the good performance of the IFA scheme in different motorcycle operating conditions. © 1963-2012 IEEE.
|
|
| 6. |
- Catelani, Marcantonio, et al.
(författare)
-
Optimizing Maintenance Policies for a Yaw System Using Reliability-Centered Maintenance and Data-Driven Condition Monitoring
- 2020
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - : IEEE. - 0018-9456 .- 1557-9662. ; 69:9, s. 6241-6249
-
Tidskriftsartikel (refereegranskat)abstract
- System downtime and unplanned outages massively affect plant productivity; therefore, the reliability, availability, maintainability, and safety (RAMS) disciplines, together with fault diagnosis and condition monitoring (CM), are mandatory in energy applications. This article focuses on the optimization of a maintenance plan for the yaw system used in an onshore wind turbine (WT). A complete reliability-centered maintenance (RCM) procedure is applied to the system to identify which maintenance action is the optimal solution in terms of cost, safety, and availability. The scope of the research is to propose a new customized decision-making diagram inside the RCM assessment to reduce the subjectivity of the procedure proposed in the standard and save the cost by optimizing maintenance decisions, making the projects more cost-efficient and cost-effective. This article concludes by proposing a new diagnostic method based on a data-driven CM system to efficiently monitor the health and detect damages in the WT by means of measurements of critical parameters of the tested system. This article highlights how a reliability analysis, during the early phase of the design, is a very helpful and powerful means to guide the maintenance decision and the data-driven CM.
|
|
| 7. |
- Chang, Lin, et al.
(författare)
-
Multisurface Interferometric Algorithm and Error Analysis With Adaptive Phase Shift Matching
- 2022
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0018-9456 .- 1557-9662. ; 71
-
Tidskriftsartikel (refereegranskat)abstract
- To simultaneously measure topographies of both surfaces of a transparent plate through wavelength-tuning interferometry at arbitrary cavity lengths, a flexible phase shift matching algorithm (FPSMA) is proposed. The FPSMA includes two parts: 1) taking the four-term third-order Nuttall window as an example, a phase demodulation approach is designed and analyzed for extracting the harmonic phases of the front surface, rear surface, and thickness variation of the measured plate and 2) based on the residual error analysis of the developed 5N-Nuttall algorithm for different cavity length coefficients M and the phase-shifting parameters N , a parameter-change technique that allows the developed phase demodulation approach is applied to arbitrary cavity lengths by adaptively changing the phase shifts and frames of the captured interferograms. By this technique, the algorithm failures due to the spectral aliasing of harmonics can be avoided effectively and conveniently, and then the correct phase demodulation can be ensured. Besides, using the developed method, when the values of N or M are chosen in advance, the corresponding available measurement ranges can be given. Besides, the relationship between the window length and the measurement limitation of the measurable thinnest optical thickness is investigated. Considering the common linear and nonlinear errors in the wavelength-shifting process, the error analysis of FPSMA is performed and discussed for situations close to reality. The comparative studies and the experimental results of two transparent parallel plates also support the performance of the developed FPSMA.
|
|
| 8. |
- Cheng, Liu, et al.
(författare)
-
EEG-CLNet : Collaborative Learning for Simultaneous Measurement of Sleep Stages and OSA Events Based on Single EEG Signal
- 2023
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - : IEEE. - 0018-9456 .- 1557-9662. ; 72
-
Tidskriftsartikel (refereegranskat)abstract
- Sleep-stage and apnea-hypopnea index (AHI) are the most important metrics in the diagnosis of sleep syndrome disease. In previous studies, these two tasks are usually implemented separately, which is both time- and resource-consuming. In this work, we propose a novel single electroencephalogram (EEG)-based collaborative learning network (EEG-CLNet) for simultaneous sleep staging and obstructive sleep apnea (OSA) event detection through multitask collaborative learning. The EEG-CLNet regards different tasks as a common unit to extract features from intragroups via both local parameter sharing and cross-task knowledge distillation (CTKD), rather than just sharing parameters or shortening the distance between different tasks. Our approach has been validated on two datasets with the same or better performance than other methods. The experimental results show that our method achieves a performance gain of 1%-5% compared with the baseline. Compared to previous works where two or even more models were required to perform sleep staging and OSA event detection, the EEG-CLNet could reduce the total number of model parameters and facilitate the model to mine the hidden relationships between different task semantic information. More importantly, it effectively alleviates the task bias problem in hard parameter sharing. As a consequence, this approach has notable potential to be a solution for a lightweight wearable sleep monitoring system in the future.
|
|
| 9. |
- Di Caro, D., et al.
(författare)
-
Quality Assessment of the Inshell Hazelnuts Based on TD-NMR Analysis
- 2020
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - : Institute of Electrical and Electronics Engineers Inc.. - 0018-9456 .- 1557-9662. ; 69:6, s. 3770-3779
-
Tidskriftsartikel (refereegranskat)abstract
- Nondestructive testing is critical in the quality detection of products. Among several techniques, time-domain nuclear magnetic resonance (TD-NMR) is gaining attention in the field of food quality control, thanks to its ability to detect liquid and solid materials, which are strictly related to the quality of some kinds of products. In this article, a novel method for the inline quality evaluation of the inshell hazelnuts, based on TD-NMR analysis, is disclosed. Different studies have been carried out on the quality control of hazelnuts or, more in general, shell fruit. They usually focus on laboratory application and the analysis of a single physical property. Conversely, the proposed method focuses on the signal processing with the aim of reducing the execution time making the procedure suitable for an inline application. Moreover, the main hidden defects are analyzed together to identify the defective nuts from the good ones in a two-class classification procedure. © 1963-2012 IEEE.
|
|
| 10. |
- Fedorov, Igor, et al.
(författare)
-
A two-layer 3D reconstruction method and calibration for multi-camera-based volumetric positioning and characterization
- 2021
-
Ingår i: IEEE Transactions on Instrumentation and Measurement. - 0018-9456 .- 1557-9662. ; 70
-
Tidskriftsartikel (refereegranskat)abstract
- A three-dimensional (3D) reconstruction method and multi-camera calibration using multiple artificial reference markers have been used for precise volumetric surveillance of fast-flying objects. The method uses a two-layer 3D reconstruction that integrates two multi-camera stereo-nodes. The fields of view of stereo nodes are directed at an acute angles to each other to provide greater coverage with the given constraints and to determine the flight characteristics of objects in 3D. The object’s flight reconstruction includes a “rough” estimation of its positions relative to selected artificial reference points in both stereo nodes separately and subsequent “refinement” of calculated positions. In this paper, we describe the proposed method and calibration technique, using a multi-camera system to measure object characteristics in 3D. The proposed method applies to volumetric surveillance in situations where it is necessary to count, track, and analyze the activities of flying objects, especially birds, using high spatial resolution.
|
|
