Title :
Fault detection and diagnosis in duals converters applied in DC drives
Author :
De Gouvêa, Marlon R. ; Baccarini, Lane M R ; Caminhas, Walmir M.
Abstract :
Summary form only given. For duals converters of AC or DC drives, faults related with them are important in relation with the available time of equipments. Besides, the speed sensors used as tachogenerator and pulse generator are important factors. This work presents a fault diagnostic and detection system for commutation, short circuit and circuit open faults. Speed sensor faults can also be detected with an automatic feedback reconfiguration. The fault diagnostic and detection system is based in the fuzzy set theory to generate inputs to the neural network responsible for fault classification, and the state observer for sensor speed fault detection. Results obtained from digital simulations conclude that the system is a simple and efficient means for the detection of the proposed faults. Other advantage is that the control system reconfiguration based on the state observers permits the drive system to operate during speed sensor faults. So, this proposed fault detection system is ideal for practical implementation.
Keywords :
DC motor drives; fault diagnosis; fuzzy set theory; neural nets; observers; power convertors; DC drives; circuit open fault; commutation; duals converters; fault classification; fault detection; fault diagnostic system; fuzzy set theory; neural network; short circuit fault; speed sensors; state observer; Analog-digital conversion; Circuit faults; Electrical fault detection; Fault detection; Fault diagnosis; Fuzzy set theory; Neural networks; Neurofeedback; Pulse generation; Sensor systems;
Conference_Titel :
Neural Networks, 2002. SBRN 2002. Proceedings. VII Brazilian Symposium on
Print_ISBN :
0-7695-1709-9
DOI :
10.1109/SBRN.2002.1181444