基于SVDI的变工况旋转机械故障诊断方法

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振动与冲击 ›› 2018, Vol. 37 ›› Issue (19) : 211-216.

论文

宋涛1,2，王瑜琳3，赵明富1,2，钟年丙1,2

作者信息 +

Fault diagnosis for rotating machineries under variable operation conditions based on SVDI

SONG Tao1,2,WANG Yulin3, ZHAO Mingfu1,2,ZHONG Nianbing1,2

Author information +

文章历史 +

摘要

旋转机械设备变工况特点导致振动特征不稳定，给故障诊断带来很大困难这一问题。提出一种基于奇异值分解插值(Singular Value Decomposition Interpolation, SVDI)的变工况故障诊断方法，构建离散工况下的振动信号样本，通过奇异值分解将样本特征矩阵分解为奇异向量、旋转矩阵和特征均值，分别对奇异向量、旋转矩阵和特征均值进行插值，再重构实测工况下的特征矩阵，最后通过特征约简、模式识别方法进行故障诊断。该方法可在没有完备样本库的条件下估计出一定范围内任意工况的振动特征，能解决旋转机械设备变工况条件下的故障诊断难题。多种转速下的齿轮箱故障诊断实例证明了该方法的有效性。

Abstract

Variable operation conditions of rotating machineries lead to unstable vibration characteristics to bring large difficulties to their fault diagnosis.Here, a method for variable conditions fault diagnosis based on the singular value decomposition interpolation (SVDI) was proposed.Firstly, vibration signal samples of rotating machinery were collected under a discrete operation condition.Then sample characteristic matrices were decomposed into singular vectors, rotation matrices and characteristic means with SVD.These singular vectors, rotation matrices and characteristic means were interpolated to reconstruct characteristic matrices under the actual measured operation condition.Finally, the fault diagnosis for rotating machinery was conducted with the feature reduction and pattern recognition method.It was shown that the proposed method can be used to estimate vibration characteristics of rotating machinery under any working condition to a certain extent when there is no complete sample base, and solve difficult fault diagnosis problems of rotating machineries under variable operation conditions.

导出引用

宋涛1,2，王瑜琳3，赵明富1,2，钟年丙1,2. 基于SVDI的变工况旋转机械故障诊断方法[J]. 振动与冲击, 2018, 37(19): 211-216

SONG Tao1,2,WANG Yulin3, ZHAO Mingfu1,2,ZHONG Nianbing1,2. Fault diagnosis for rotating machineries under variable operation conditions based on SVDI[J]. Journal of Vibration and Shock, 2018, 37(19): 211-216

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