Sensors and Fault Diagnostics in Power System
The assessment of key apparatuses’ adequate technical conditions is crucial in the delivery of reliable and continuous electric power to customers. To meet this requirement, any fault in the power system must be detected and diagnosed as early as possible, with particular emphasis on the precision o...
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| Format: | Online |
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| Jezik: | engleski |
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Online pristup: | ONIX_20250220_9783725822430_180 |
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| collection | Directory of Open Access Books |
| description | The assessment of key apparatuses’ adequate technical conditions is crucial in the delivery of reliable and continuous electric power to customers. To meet this requirement, any fault in the power system must be detected and diagnosed as early as possible, with particular emphasis on the precision of the diagnostic process. Various online and offline diagnostic methods are widely applied for the early detection of system malfunctions, alongside a number of different sensors, which may be used to capture selected physical quantities indicating the type of potential faults. A specific fault diagnostic process is typically carried out by experts in the field; however, artificial intelligence (AI)-based systems are increasingly being proposed to support decision making related to this task. An essential step in fault diagnostic processes is signal analysis, and this is supported by features including (but not limited to) signal processing, feature extraction, modeling, and prediction methods. In this context, this Special Issue includes ten high-quality papers dealing with the main problems currently related to sensors and fault diagnostics in power system engineering. |
| format | Online |
| id | doab-20.500.12854ir-152816 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1528162025-02-20T13:07:08Z Sensors and Fault Diagnostics in Power System Kunicki, Michał Fulneček, Jan Rozga, Pawel magnetic field differential method optimal step size rounding error truncation error electrical contact specific resistivity contact resistance constriction resistance fritting diagnostic crossed bars measurement mineral oil natural ester oil power transformer dielectric properties measurement dynamic viscosity condition assessment mixture oil accelerated aging diagnostic process sensor failure fault-tolerant control DC microgrids attracting ellipsoid method instrument transformers accuracy Rogowski coil modelling uncertainty industrial oriented outlier detection the Minorization–Maximization algorithm localization power system high voltage measurements fault diagnostics converter transformer current fault diagnosis improved hunter–prey optimization multi-strategy improved MFCC voiceprint signal capacitive electric field sensor capacitive divider high-voltage measurement system switching transients transient overvoltages equivalent error PMU RBF DFT synchrophasors phase and amplitude estimation n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology The assessment of key apparatuses’ adequate technical conditions is crucial in the delivery of reliable and continuous electric power to customers. To meet this requirement, any fault in the power system must be detected and diagnosed as early as possible, with particular emphasis on the precision of the diagnostic process. Various online and offline diagnostic methods are widely applied for the early detection of system malfunctions, alongside a number of different sensors, which may be used to capture selected physical quantities indicating the type of potential faults. A specific fault diagnostic process is typically carried out by experts in the field; however, artificial intelligence (AI)-based systems are increasingly being proposed to support decision making related to this task. An essential step in fault diagnostic processes is signal analysis, and this is supported by features including (but not limited to) signal processing, feature extraction, modeling, and prediction methods. In this context, this Special Issue includes ten high-quality papers dealing with the main problems currently related to sensors and fault diagnostics in power system engineering. 2025-02-20T13:07:05Z 2025-02-20T13:07:05Z 2024 book ONIX_20250220_9783725822430_180 9783725822430 9783725822447 https://directory.doabooks.org/handle/20.500.12854/152816 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/10055 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-2244-7 10.3390/books978-3-7258-2244-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725822430 9783725822447 194 Basel open access |
| spellingShingle | magnetic field differential method optimal step size rounding error truncation error electrical contact specific resistivity contact resistance constriction resistance fritting diagnostic crossed bars measurement mineral oil natural ester oil power transformer dielectric properties measurement dynamic viscosity condition assessment mixture oil accelerated aging diagnostic process sensor failure fault-tolerant control DC microgrids attracting ellipsoid method instrument transformers accuracy Rogowski coil modelling uncertainty industrial oriented outlier detection the Minorization–Maximization algorithm localization power system high voltage measurements fault diagnostics converter transformer current fault diagnosis improved hunter–prey optimization multi-strategy improved MFCC voiceprint signal capacitive electric field sensor capacitive divider high-voltage measurement system switching transients transient overvoltages equivalent error PMU RBF DFT synchrophasors phase and amplitude estimation n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology Sensors and Fault Diagnostics in Power System |
| title | Sensors and Fault Diagnostics in Power System |
| title_full | Sensors and Fault Diagnostics in Power System |
| title_fullStr | Sensors and Fault Diagnostics in Power System |
| title_full_unstemmed | Sensors and Fault Diagnostics in Power System |
| title_short | Sensors and Fault Diagnostics in Power System |
| title_sort | sensors and fault diagnostics in power system |
| topic | magnetic field differential method optimal step size rounding error truncation error electrical contact specific resistivity contact resistance constriction resistance fritting diagnostic crossed bars measurement mineral oil natural ester oil power transformer dielectric properties measurement dynamic viscosity condition assessment mixture oil accelerated aging diagnostic process sensor failure fault-tolerant control DC microgrids attracting ellipsoid method instrument transformers accuracy Rogowski coil modelling uncertainty industrial oriented outlier detection the Minorization–Maximization algorithm localization power system high voltage measurements fault diagnostics converter transformer current fault diagnosis improved hunter–prey optimization multi-strategy improved MFCC voiceprint signal capacitive electric field sensor capacitive divider high-voltage measurement system switching transients transient overvoltages equivalent error PMU RBF DFT synchrophasors phase and amplitude estimation n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology |
| topic_facet | magnetic field differential method optimal step size rounding error truncation error electrical contact specific resistivity contact resistance constriction resistance fritting diagnostic crossed bars measurement mineral oil natural ester oil power transformer dielectric properties measurement dynamic viscosity condition assessment mixture oil accelerated aging diagnostic process sensor failure fault-tolerant control DC microgrids attracting ellipsoid method instrument transformers accuracy Rogowski coil modelling uncertainty industrial oriented outlier detection the Minorization–Maximization algorithm localization power system high voltage measurements fault diagnostics converter transformer current fault diagnosis improved hunter–prey optimization multi-strategy improved MFCC voiceprint signal capacitive electric field sensor capacitive divider high-voltage measurement system switching transients transient overvoltages equivalent error PMU RBF DFT synchrophasors phase and amplitude estimation n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology |
| url | ONIX_20250220_9783725822430_180 |