机械故障诊断的稀疏特征提取方法

doi:10.3969/j.issn.1001-2400.2018.02.026

西安电子科技大学学报

机械故障诊断的稀疏特征提取方法

贺王鹏;孙伟;苏博;闫允一;郭宝龙

(西安电子科技大学空间科学与技术学院，陕西西安 710071)

收稿日期:2017-06-12 出版日期:2018-04-20 发布日期:2018-06-06
作者简介:贺王鹏(1989-)，男，讲师，E-mail：hewp@xidian.edu.cn
基金资助:
国家自然科学基金资助项目(61671356)；中央高校基本科研业务费专项资金资助项目(20103176447)；西安电子科技大学新实验开发与新实验设备研制及实验教学改革资助项目(JG1608)

Sparse feature extraction technique and its applications to machinery fault diagnosis

HE Wangpeng;SUN Wei;SU Bo;YANG Yunyi;GUO Baolong

(School of Aerospace Science ＆ Technology, Xidian Univ., Xi'an 710071, China)

Received:2017-06-12 Online:2018-04-20 Published:2018-06-06

摘要/Abstract

摘要：

针对旋转机械的周期性稀疏故障特征提取问题，提出了一种周期重叠簇稀疏信号优化特征提取算法．该算法根据机械故障诊断周期性特征提取问题构造了有效的稀疏优化目标函数，该目标函数中的正则项(惩罚函数)选用非凸惩罚函数来增强周期性特征的稀疏性，并且证明了非凸可控化参数在一定约束条件下可以保证目标函数整体为凸．基于优控极小化方法求解所构造的优化问题，推导出高效的快速迭代收敛数值算法，该求解算法最终收敛于优化问题的全局最优解．将所研究的周期重叠簇稀疏信号优化特征提取算法应用于仿真信号，定量分析了其相对于对比算法的优越性．最后，将所研究的周期重叠簇稀疏信号优化特征提取算法应用于轴承故障特征提取中，结果表明，该算法其可以有效地提取稀疏微弱故障特征．

关键词: 旋转机械, 故障诊断, 凸优化, 稀疏特征提取

Abstract:

To address the problem of extracting periodic-group-sparse features for the purpose of detecting machinery faults, the periodic overlapping group sparsity (POGS) method is thoroughly investigated. The POGS method formulates a convex optimization problem to extract periodic sparse features based on the prior knowledge of machinery fault diagnosis. The non-convex penalty functions are employed to further enhance the sparsity of useful fault features. Moreover, the convexity condition of the POGS optimization problem is provided. A fast iterative algorithm is given for its optimal solution based on the majorization-minimization approach. A simulated signal is formulated to verify the performance of the POGS method for periodic feature extraction. Finally, the POGS method is applied to process experimental data for detecting bearing faults. The estimated results demonstrate that the POGS method can effectively extract the periodic-group-sparse fault features.

Key words: rotating machines, fault diagnosis, convex optimization, sparse feature extraction

贺王鹏;孙伟;苏博;闫允一;郭宝龙. 机械故障诊断的稀疏特征提取方法[J]. 西安电子科技大学学报, 2018, 45(2): 154-159.

HE Wangpeng;SUN Wei;SU Bo;YANG Yunyi;GUO Baolong. Sparse feature extraction technique and its applications to machinery fault diagnosis[J]. Journal of Xidian University, 2018, 45(2): 154-159.

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机械故障诊断的稀疏特征提取方法

Sparse feature extraction technique and its applications to machinery fault diagnosis

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