Gear Fault Feature Extraction Method Based on Adaptive MCKD and FSWT

Abstract

Abstract:

Aiming at the problem that denoising effect of the MCKD was subject to order of the filter，a adaptive MCKD method was proposed，aiming at the deficiency of FSWT extracting impulse fault features from strong noise background，a fault feature extraction method for gears was proposed based on adaptive MCKD method and FSWT. Firstly，by using adaptive MCKD，the noise in the gear vibration signals was reduced，then the denoised signals were decomposed by applying FSWT to extract fault characteristics，gear fault vibration signals analysis demonstrates the effectiveness of the method.

Key words: gear fault diagnosis, maximum correlated kurtosis deconvolution(MCKD), adaptive, frequency slice wavelet transform(FSWT)

摘要：

针对最大相关峭度解卷积(MCKD)降噪效果受滤波器阶数影响的问题，提出了自适应MCKD方法。针对频率切片小波变换(FSWT)在强背景噪声中提取冲击故障特征的不足，提出了自适应MCKD和FSWT相结合的齿轮故障特征提取方法。首先用自适应MCKD对噪声齿轮信号进行降噪处理，然后对降噪后的信号进行频率切片小波变换和故障特征提取。齿轮故障诊断实例的分析结果验证了该方法的有效性。

CLC Number:

Zhong Xianyou, Zhao Chunhua, Tian Hongliang, Chen Baojia, Zhao Meiyun. Gear Fault Feature Extraction Method Based on Adaptive MCKD and FSWT[J]. China Mechanical Engineering, 2014, 25(21): 2880-2885.

钟先友, 赵春华, 田红亮, 陈保家, 赵美云. 基于自适应最大相关峭度解卷积和频率切片小波变换的齿轮故障特征提取[J]. 中国机械工程, 2014, 25(21): 2880-2885.

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