TY  - CHAP
AU  - Ian Kuiler
AU  - Marco Adonis
AU  - Atanda Raji
ED  - Constantin Volosencu
Y1  - 2018-11-05
PY  - 2018
T1  - Preventive Maintenance and Fault Detection for Wind Turbine Generators Using a Statistical Model
N2  - 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.
BT  - Fault Detection and Diagnosis
SP  - Ch. 2
UR  - https://doi.org/10.5772/intechopen.80071
DO  - 10.5772/intechopen.80071
SN  - 978-1-78984-437-5
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-25
ER  -