"Fault Detection and Diagnosis" ed. by Constantin Volosencu

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"Fault Detection and Diagnosis" ed. by Constantin Volosencu
ITExLi | 2018 | ISBN: 1789844371 9781789844375 1789844363 9781789844368 1838818316 9781838818319 | 111 pages | PDF | 12 MB

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 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.

Contents
1. Fault Diagnosis of Hybrid Computing Systems Using Chaotic-Map Method
2. Preventive Maintenance and Fault Detection for Wind Turbine Generators Using a Statistical Model
3. Hybrid Fault Diagnosis Method Based on Mechanical-Electrical Intersectional Characteristics for Generators
4. A Comparative Study on Some Fault Diagnosis Techniques in Three-Phase Inverter Fed Induction Motors
5. Fault Residuals Based on Distributed Discrete-Time Linear Kalman Filtering

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