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This paper presents an artificial immune system based classification rules generation for fault diagnosis of induction motors. To implement the proposed method effectively, a feature extraction and fuzzificiation processes are used for choosing fault-related attributes from motor current signals. The idea behind the method is mainly based on both concepts of data mining and artificial immune system...
In this study, an FPGA based method has been presented for detection of broken rotor bar faults occurred in induction motors. The proposed method takes one phase current signal and extracts feature signal by applying Hilbert transform. Each state of finite state machine is obtained calculating the entropy value on feature signal. The state transition matrix is constructed in real time on FPGA environment...
The voltage model used for direct vector control has in the flux calculation process an open integration problem, which is generally solved with a feedback loop. In this paper, a new design method is developed for the feedback loop of the integrator. The method, as apart from standards in the literature, uses a fuzzy controller. Fuzzy controllers are knowledge-based systems that include fuzzy rules...
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