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针对永磁电机电磁噪声定位问题，提出一种基于声源波达方位估计的电磁噪声诊断方法。该方法在电机由变频器供电的运行工况下进行多信道噪声采样，通过先验频率数据识别各噪声信道中的电机电磁噪声源特征，结合DBSCAN聚类算法和能量门限，有效提取窄带信号。采用改进的噪声子空间重构算法——MCT-IRNSMUSIC对窄带信号进行波达方位（direction of arrival,DOA）估计，并通过自适应加权得到最终DOA估计结果。该算法拓展了阵列孔径，实现了针对多相干信号源的有效方位角估计，提高了混响环境下的准确性。仿真对比和实验结果表明，相较于传统算法，该方法具有更高的准确性和鲁棒性，其噪声源定位准确率可达96.2%，在工程应用中具有参考价值。
Abstract：A diagnosis method based on the direction of sound source wave arrival is proposed to address the issue of electromagnetic noise localization in permanent magnet motors during operation. This method conducts multi-channel noise sampling under the operating conditions of the motor when it is powered by an inverter. It identifies the characteristics of electromagnetic noise sources in each noise channel based on prior frequency data and combines the DBSCAN clustering algorithm with an energy threshold to effectively extract narrowband signals. The improved noise subspace reconstruction algorithm——MCT-IRNSMUSIC is employed to estimate the direction of arrival(DOA) of narrowband signals, and the final DOA estimation result is obtained via adaptive weighting. The algorithm extends the array aperture, achieving effective azimuth estimation for multi-coherent signal sources and improving accuracy in reverberant environments. Simulation comparisons and experimental results demonstrate that this method exhibits higher accuracy and robustness compared to traditional algorithms, with a noise source localization accuracy of 96.2%, which has reference value in engineering applications.
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基本信息:
DOI：10.11857/j.issn.1674-5124.2024050115
中图分类号:TM351
引用信息:
[1]沈振燚,王子辉,翁晓伟,等.应用波达方位估计的电机电磁噪声诊断方法研究[J].中国测试,2026,52(03):25-33.DOI:10.11857/j.issn.1674-5124.2024050115.
基金信息:
浙江省教育厅一般科研项目(Y202351949); 浙江科技大学研究生科研创新基金(2023yjskc06)
2024-05-25
2024-07-09
2026-03-31
2026-03-31