RV reducer fault diagnosis based on order tracking and improved wavelet threshold noise reduction
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摘要: 针对RV减速器在进行摆动疲劳试验时采集到的振动信号存在振动源复杂，噪声影响强，非线性变换等特点，利用传统的傅里叶变换（fast fourier transform，FFT）分析时存在“频率模糊”现象，不能准确地提取故障磨损点。针对上述问题，提出了一种阶次跟踪分析结合改进小波阈值降噪方法对RV减速器在疲劳实验时采集到的振动信号进行故障特征提取。首先利用阶次跟踪方法对采集到的非平稳时域振动信号进行等角度域转化；再利用改进小波阈值降噪法对等角度域信号进行阈值降噪；对得到的降噪后的等角度域信号进行FFT变换，得到阶次图。对比传统的小波降噪分析结果，该方法可以有效地提取出RV减速器在摆动疲劳实验中内部零部件发生的故障信息，为变转速旋转机械的故障诊断提供了基础。Abstract: In view of the characteristics of the vibration signal collected during the swing fatigue test of the RV reducer, the vibration source is complex, the noise influence is strong, and the nonlinear transformation is used. phenomenon, the fault wear point cannot be accurately extracted. In view of the above problems, this paper proposes an order tracking analysis combined with an improved wavelet threshold noise reduction method to extract the fault features of the vibration signal collected during the fatigue test of the RV reducer. Firstly, the collected non-stationary time-domain vibration signal is transformed into the equi-angle domain by the order tracking method; then the equi-angle domain signal is denoised by threshold using the improved wavelet threshold noise reduction method; The signal is subjected to FFT transformation to obtain an order map. Compared with the traditional wavelet noise reduction analysis results, the method can effectively extract the fault information of the internal parts of the RV reducer in the swing fatigue experiment, which provides a basis for the fault diagnosis of variable-speed rotating machinery.
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表 2 行星摆线针轮减速器故障信号的3种阈值函数的降噪评价指标
评价指标 硬阈值 软阈值 改进阈值 SNR 0.011 5 0.556 1 1.286 2 RMSE 0.025 55 0.023 99 0.022 06 
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