Abstract
This paper explores the idea of detecting uniform permanent-magnet (PM) demagnetization by using acoustic noises in order to develop a reliable PM synchronous machine (PMSM) controller. A flux-based acoustic noise model is proposed to demonstrate that demagnetization will induce acoustic noise containing abnormal frequency. This paper will also analyze online PM demagnetization detection by using a back propagation neural network (BPNN) with acoustic noise data. First, seven objective and psychoacoustic indicators are proposed to evaluate the acoustic noise of healthy and demagnetized PMSMs under different speed and load conditions. Next, a novel BPNN-based PM demagnetization detection method is proposed. In this method, the PM demagnetization is detected by means of comparing the measured acoustic signal of PMSM with an acoustic signal library of seven acoustical indicators. The proposed PM demagnetization detection approach is experimentally evaluated. Unlike other approaches, this is a noninvasive method and is independent of internal motor parameters. The aforementioned seven indicators can process nonlinear signals and are used to comprehensively reflect noise quality.
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