基于奇异值差分谱和SDP图像相关分析的故障诊断方法

Fault Diagnosis Method Based on Difference Spectrum of Singular Value and SDP Image Correlation Analysis

为有效利用旋转机械振动信号进行故障诊断,提出了基于奇异值差分谱和SDP(Symmetrized Dot Pattern)图像相关分析的故障诊断方法。该方法首先通过奇异值差分谱对振动信号进行降噪处理以消除噪声的干扰;然后利用SDP方法对降噪后信号进行变换,得到不同故障状态下的极坐标雪花图像;最后利用正常状态和故障状态下的SDP图像之间的相关系数来判断故障状态。齿轮典型故障的诊断结果证明,该方法能快速准确地分辨出齿轮不同的故障状态,具有一定的优势。

In order to take full advantage of rotating machine vibration signal to fault diagnosis, a fault diagnosis method is introduced based on difference spectrum of singular values and symmetrized dot pattern （ SDP ） image correlation analysis. Firstly, the time domain waveform is denoised by difference spectrum of singular values to eliminate the effect of noise. And then, the signal after de- noising was transformed into snow images in polar coordinates through the SDP method. Finally, using the correlation coefficient of SDP image in different states to diagnosis the fault state. Experimental results of gear typical fault diagnosis show that the proposed method can identify different states of gear and has a certain superiority.