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Yan J, Chen C, Wu Z, Ding X, Lou L. An Acoustic Localization Sensor Based on MEMS Microphone Array for Partial Discharge. SENSORS (BASEL, SWITZERLAND) 2023; 23:1077. [PMID: 36772119 PMCID: PMC9919250 DOI: 10.3390/s23031077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 01/08/2023] [Accepted: 01/11/2023] [Indexed: 06/18/2023]
Abstract
Partial discharge (PD) localization is important for monitoring and maintaining high-voltage equipment, which can help to prevent accidents. In this work, an acoustic localization sensor based on microelectromechanical system (MEMS) microphone array is proposed, which can detect and locate the partial discharge through a beam-forming algorithm. The MEMS microphone array consists of eight commercial MEMS microphones (SPV08A0LR5H-1, Knowles Electronics, IL, USA) with an aperture size of about 0.1 m × 0.1 m, allowing for a small hardware size and low cost. In order to optimize the acoustic performance of the array, a random array topology is designed. The simulation analysis indicates that the designed random topology is superior to several commonly used topologies. In terms of the localization algorithm, a deconvolution method called Fourier-based fast iterative shrinkage thresholding algorithm (FFT-FISTA) is applied. Simulation and experiment results demonstrate that FFT-FISTA used in the proposed acoustic localization sensor has significant advantages over the conventional beam-forming algorithm on spatial resolution and sidelobe suppression. Experimental results also show that the average localization error of the proposed scheme is about 0.04 m, which can meet the demands of practical application.
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Affiliation(s)
- Jiaming Yan
- School of Microelectronics, Shanghai University, Shanghai 201800, China
| | - Caihui Chen
- The Shanghai Industrial μTechnology Research Institute, Shanghai 201899, China
| | - Zhipeng Wu
- The Shanghai Industrial μTechnology Research Institute, Shanghai 201899, China
| | - Xiaoxia Ding
- School of Microelectronics, Shanghai University, Shanghai 201800, China
| | - Liang Lou
- School of Microelectronics, Shanghai University, Shanghai 201800, China
- The Shanghai Industrial μTechnology Research Institute, Shanghai 201899, China
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Fé J, Correia SD, Tomic S, Beko M. Swarm Optimization for Energy-Based Acoustic Source Localization: A Comprehensive Study. SENSORS (BASEL, SWITZERLAND) 2022; 22:1894. [PMID: 35271040 PMCID: PMC8914714 DOI: 10.3390/s22051894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 02/23/2022] [Accepted: 02/24/2022] [Indexed: 06/14/2023]
Abstract
In the last decades, several swarm-based optimization algorithms have emerged in the scientific literature, followed by a massive increase in terms of their fields of application. Most of the studies and comparisons are restricted to high-level languages (such as MATLAB®) and testing methods on classical benchmark mathematical functions. Specifically, the employment of swarm-based methods for solving energy-based acoustic localization problems is still in its inception and has not yet been extensively studied. As such, the present work marks the first comprehensive study of swarm-based optimization algorithms applied to the energy-based acoustic localization problem. To this end, a total of 10 different algorithms were subjected to an extensive set of simulations with the following aims: (1) to compare the algorithms' convergence performance and recognize novel, promising methods for solving the problem of interest; (2) to validate the importance (in convergence speed) of an intelligent swarm initialization for any swarm-based algorithm; (3) to analyze the methods' time efficiency when implemented in low-level languages and when executed on embedded processors. The obtained results disclose the high potential of some of the considered swarm-based optimization algorithms for the problem under study, showing that these methods can accurately locate acoustic sources with low latency and bandwidth requirements, making them highly attractive for edge computing paradigms.
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Affiliation(s)
- João Fé
- COPELABS, Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, 1749-024 Lisboa, Portugal; (J.F.); (S.T.)
- VALORIZA—Research Centre for Endogenous Resource Valorization, Instituto Politécnico de Portalegre, Campus Politécnico n.10, 7300-555 Portalegre, Portugal
| | - Sérgio D. Correia
- COPELABS, Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, 1749-024 Lisboa, Portugal; (J.F.); (S.T.)
- VALORIZA—Research Centre for Endogenous Resource Valorization, Instituto Politécnico de Portalegre, Campus Politécnico n.10, 7300-555 Portalegre, Portugal
| | - Slavisa Tomic
- COPELABS, Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, 1749-024 Lisboa, Portugal; (J.F.); (S.T.)
| | - Marko Beko
- Instituto de Telecomunicações, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal;
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A Study of Multilayer Perceptron Networks Applied to Classification of Ceramic Insulators Using Ultrasound. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11041592] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Interruptions in the supply of electricity cause numerous losses to consumers, whether residential or industrial and may result in fines being imposed on the regulatory agency’s concessionaire. In Brazil, the electrical transmission and distribution systems cover a large territorial area, and because they are usually outdoors, they are exposed to environmental variations. In this context, periodic inspections are carried out on the electrical networks, and ultrasound equipment is widely used, due to non-destructive analysis characteristics. Ultrasonic inspection allows the identification of defective insulators based on the signal interpreted by an operator. This task fundamentally depends on the operator’s experience in this interpretation. In this way, it is intended to test machine learning applications to interpret ultrasound signals obtained from electrical grid insulators, distribution, class 25 kV. Currently, research in the area uses several models of artificial intelligence for various types of evaluation. This paper studies Multilayer Perceptron networks’ application to the classification of the different conditions of ceramic insulators based on a restricted database of ultrasonic signals recorded in the laboratory.
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Ezugwu AE. Nature-inspired metaheuristic techniques for automatic clustering: a survey and performance study. SN APPLIED SCIENCES 2020. [DOI: 10.1007/s42452-020-2073-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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Chai H, Phung BT, Mitchell S. Application of UHF Sensors in Power System Equipment for Partial Discharge Detection: A Review. SENSORS 2019; 19:s19051029. [PMID: 30823431 PMCID: PMC6427733 DOI: 10.3390/s19051029] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 02/22/2019] [Accepted: 02/24/2019] [Indexed: 12/05/2022]
Abstract
Condition monitoring of an operating apparatus is essential for lifespan assessment and maintenance planning in a power system. Electrical insulation is a critical aspect to be monitored, since it is susceptible to failure under high electrical stress. To avoid unexpected breakdowns, the level of partial discharge (PD) activity should be continuously monitored because PD occurrence can accelerate the aging process of insulation in high voltage equipment and result in catastrophic failure if the associated defects are not treated at an early stage. For on-site PD detection, the ultra-high frequency (UHF) method was employed in the field and showed its effectiveness as a detection technique. The main advantage of the UHF method is its immunity to external electromagnetic interference with a high signal-to-noise ratio, which is necessary for on-site monitoring. Considering the detection process, sensors play a critical role in capturing signals from PD sources and transmitting them onto the measurement system. In this paper, UHF sensors applied in PD detection were comprehensively reviewed. In particular, for power transformers, the effects of the physical structure on UHF signals and practical applications of UHF sensors including PD localization techniques were discussed. The aim of this review was to present state-of-the-art UHF sensors in PD detection and facilitate future improvements in the UHF method.
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Affiliation(s)
- Hua Chai
- School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney 2052, NSW, Australia.
| | - B T Phung
- School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney 2052, NSW, Australia.
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Peng W, Zhao Q, Chen M, Piao J, Gao W, Gong X, Chang J. An innovative "unlocked mechanism" by a double key avenue for one-pot detection of microRNA-21 and microRNA-141. Am J Cancer Res 2019; 9:279-289. [PMID: 30662567 PMCID: PMC6332803 DOI: 10.7150/thno.28474] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 12/04/2018] [Indexed: 12/19/2022] Open
Abstract
The accurate and quantitative detection of microRNAs (miRNAs) as next-generation, reliable biomarkers will provide vital information for cancer research and treatment. However, their unique, intrinsic features pose quite a challenge for miRNA profiling, especially for multiplexed detection. Thus, there is a strong and an ever-growing need to develop an accurate, simple, sensitive and specific miRNA sensing method. Methods: In this study, a simple and novel sensor is presented that uses a flow cytometry (FCM) method based on the double key "unlocked mechanism" and a fluorescence enrichment signal amplification strategy. The "unlocked mechanism" was cleverly designed via using hairpin DNA probes (HDs) labeled by fluorescent particles (FS) as the lock to block part of them, which can specifically hybridize with the probe on polystyrene microparticles (PS). The target miRNA and duplex-specific nuclease (DSN) forming the double key can specifically open the HDs and cleave a single-stranded DNA (ssDNA) into DNA/RNA dimers circularly in order to unlock the special part of the HDs to be specially enriched further on the PS. Results: The designed sensor with a hairpin structure and DSN special performance was found to have a high specificity. The circularly unlocking fluorescent probes and fluorescent signal enrichment can be beneficial for achieving a high sensitivity with a detection limit of 3.39 fM for miRNA-21. Meanwhile, the performance of multiplexing was estimated by simultaneous detection of miR-21 and miR-141, and the method also allowed for miR-21 detection in breast cancer blood samples. Conclusion: The designed sensor based on an "unlocked mechanism" and a signal enrichment strategy resulted in a one-pot, highly specific and sensitive detection of multiplex miRNAs. The whole detection without the need for a complex purification process is based on a FCM and is expected to have a great value in cancer diagnosis and biomedical research.
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Xiong J, Wang Y, Ma GM, Zhang Q, Zheng SS. Field Applications of Ultra High Frequency Techniques for Defect Detection in GIS. SENSORS (BASEL, SWITZERLAND) 2018; 18:s18082425. [PMID: 30049935 PMCID: PMC6111932 DOI: 10.3390/s18082425] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 06/08/2023]
Abstract
The reliable and stable operation of power apparatus is important for the development of GIS. It is important to utilize condition monitoring technologies and anticipate possible failures in advance. Many papers have been published about the partial discharge detection with UHF or X-ray in laboratory, but seldom in field application. Thus, many engineers at project sites are not familiar with the current professional diagnosis techniques. Recently, during the GIS routine data analysis obtained by partial discharge online monitoring system, it was found that the UHF monitoring signals' developing trend of the 220 kV GIS No. 2 high-voltage side of transformer in phase C at an actual station was abnormal and needed further detection. In order to precisely investigate the problem and then guide the operation and maintenance activities, a series of professional diagnoses were conducted. Three new types of partial discharge detection and positioning methods were applied for accuracy, including UHF partial discharge detection based on multi-stage amplified signal demodulation and multiple weighted averages processing; the partial discharge detection based on the signal radiation hole of insulation disk at the ground connection; and the positioning method based on UHF-SHF. After a series of troubleshooting works, the partial discharge defects have been diagnosed, and the case can be referred in the field monitoring of GIS.
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Affiliation(s)
- Jun Xiong
- Guangzhou Power Supply Co., Ltd., Guangzhou 510620, China.
| | - Yuan Wang
- Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China.
| | - Guo-Ming Ma
- Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China.
| | - Qiang Zhang
- Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China.
| | - Shu-Sheng Zheng
- Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China.
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Radio-Frequency Localization of Multiple Partial Discharges Sources with Two Receivers. SENSORS 2018; 18:s18051410. [PMID: 29751527 PMCID: PMC5982690 DOI: 10.3390/s18051410] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 04/27/2018] [Accepted: 04/28/2018] [Indexed: 11/30/2022]
Abstract
Spatial localization of emitting sources is especially interesting in different fields of application. The focus of an earthquake, the determination of cracks in solid structures, or the position of bones inside a body are some examples of the use of multilateration techniques applied to acoustic and vibratory signals. Radar, GPS and wireless sensors networks location are based on radiofrequency emissions and the techniques are the same as in the case of acoustic emissions. This paper is focused on the determination of the position of sources of partial discharges in electrical insulation for maintenance based on the condition of the electrical equipment. The use of this phenomenon is a mere example of the capabilities of the proposed method but it is very representative because the emission can be electromagnetic in the VHF and UHF ranges or acoustic. This paper presents a method to locate more than one source in space with only two receivers, one of them in a fixed position and the other describing a circumference around the first one. The signals arriving from the different sources to the antennas are first separated using a classification technique based on their spectral components. Then, the individualized time differences of arrival (TDOA) from the sources collected at different angles describe a function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive these functions for any source analytically with the position of the source as unknown parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements of the TDOA to obtain the parameters of the position of each source. Finally, the technique is extended to the localization of the emitter in three dimensions.
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