Fault Detection and Diagnosis

This book offers a selection of papers in the field of fault detection and diagnosis, promoting new research results in the field, which come to join other publications in the literature. Authors from countries of four continents: United States of America, South Africa, China, India, Algeria and Cro...

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Taal:Engels
Gepubliceerd in: IntechOpen 2023
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collection Directory of Open Access Books
description This book offers a selection of papers in the field of fault detection and diagnosis, promoting new research results in the field, which come to join other publications in the literature. Authors from countries of four continents: United States of America, South Africa, China, India, Algeria and Croatia published worked examples and case studies resulting from their research in the field. Fault detection and diagnosis has a great importance in all industrial processes, to assure the monitoring, maintenance and repair of the complex processes, including all hardware, firmware and software. The book has four sections, determined by the application domain and the methods used: 1. Hybrid Computing Systems, 2. Power Systems, 3. Power Electronics and 4. Kalman Filtering. In the first section, the readers will find a technical report on fault diagnosis of hybrid computing systems, based on the chaotic-map method that uses the exponential divergence and wide Fourier properties of the trajectories, combined with memory allocations and assignments. In the second section, two chapters are included: one of them presents a study on preventive maintenance and fault detection for wind turbine generators using statistical models and the second chapter presents a technical report on fault diagnosis for turbo-generators, based on the mechanical-electrical intersectional characteristics. The third section contains a technical report that presents some techniques of detection and localization of open-circuit faults in a three-phase voltage source inverter fed induction motor. The fourth section presents a theoretical study on the application of distributed discrete-time linear Kalman filtering with decentralized structure of sensors in fault residual generation.
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spelling doab-20.500.12854ir-1301382024-04-04T19:19:49Z Fault Detection and Diagnosis Volosencu, Constantin fault diagnosis, wind turbine, induction motor, gpu, distributed computing, kalman filtering thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling This book offers a selection of papers in the field of fault detection and diagnosis, promoting new research results in the field, which come to join other publications in the literature. Authors from countries of four continents: United States of America, South Africa, China, India, Algeria and Croatia published worked examples and case studies resulting from their research in the field. Fault detection and diagnosis has a great importance in all industrial processes, to assure the monitoring, maintenance and repair of the complex processes, including all hardware, firmware and software. The book has four sections, determined by the application domain and the methods used: 1. Hybrid Computing Systems, 2. Power Systems, 3. Power Electronics and 4. Kalman Filtering. In the first section, the readers will find a technical report on fault diagnosis of hybrid computing systems, based on the chaotic-map method that uses the exponential divergence and wide Fourier properties of the trajectories, combined with memory allocations and assignments. In the second section, two chapters are included: one of them presents a study on preventive maintenance and fault detection for wind turbine generators using statistical models and the second chapter presents a technical report on fault diagnosis for turbo-generators, based on the mechanical-electrical intersectional characteristics. The third section contains a technical report that presents some techniques of detection and localization of open-circuit faults in a three-phase voltage source inverter fed induction motor. The fourth section presents a theoretical study on the application of distributed discrete-time linear Kalman filtering with decentralized structure of sensors in fault residual generation. 2023-12-01T16:53:33Z 2023-12-01T16:53:33Z 2018 book ONIX_20231201_9781789844375_1247 9781789844375 9781789844368 9781838818319 https://directory.doabooks.org/handle/20.500.12854/130138 eng image/jpeg n/a https://www.intechopen.com/books/7501 https://mts.intechopen.com/storage/books/7501/authors_book/authors_book.pdf IntechOpen IntechOpen 10.5772/intechopen.76272 10.5772/intechopen.76272 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9781789844375 9781789844368 9781838818319 IntechOpen 128 open access
spellingShingle fault diagnosis, wind turbine, induction motor, gpu, distributed computing, kalman filtering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
Fault Detection and Diagnosis
title Fault Detection and Diagnosis
title_full Fault Detection and Diagnosis
title_fullStr Fault Detection and Diagnosis
title_full_unstemmed Fault Detection and Diagnosis
title_short Fault Detection and Diagnosis
title_sort fault detection and diagnosis
topic fault diagnosis, wind turbine, induction motor, gpu, distributed computing, kalman filtering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
topic_facet fault diagnosis, wind turbine, induction motor, gpu, distributed computing, kalman filtering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
url ONIX_20231201_9781789844375_1247