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Acoustic Noise-Based Uniform Permanent-Magnet Demagnetization Detection in SPMSM for High-Performance PMSM Drive

机译:基于声学噪声的均匀永磁体退缩检测SPMSM高性能PMSM驱动器

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摘要

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.
机译:本文探讨了通过使用声噪声来检测均匀永磁体(PM)退磁的想法,以便开发可靠的PM同步机(PMSM)控制器。提出了一种基于助焊剂的声学噪声模型,以证明退磁将诱导包含异常频率的声学噪声。本文还将通过使用带有声噪声数据的后传播神经网络(BPNN)来分析在线PM脱磁检测。首先,提出了七种目标和心理声学指标,以评估不同速度和负载条件下健康和消磁PMSM的声学噪声。接下来,提出了一种新的基于BPNN的PM去磁检测方法。在该方法中,通过将PMSM的测量声信号与七个声学指示器的声学信号库进行比较,通过比较PMSM的测量声信号来检测PM去磁。实验评估所提出的PM退磁检测方法。与其他方法不同,这是一种非侵入性方法,独立于内部电机参数。上述七个指示器可以处理非线性信号,并用于全面反映噪声质量。

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