Fault diagnosis method of NC turret based on PSO⁃SVM and time sequence

被引：0

作者：

Luo W. ^{[1
,2
]}

Lu B. ^{[3
]}

Chen F. ^{[4
]}

Ma T. ^{[1
,2
]}

机构：

[1] Key Laboratory of CNC Equipment Reliability, Ministry of Education, Jilin University, Changchun

[2] College of Mechanical and Aerospace Engineering, Jilin University, Changchun

[3] Changchun Equipment & Technology Research Institute, Changchun

[4] Sino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen

来源：

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2022年 / 52卷 / 02期

关键词：

Fault diagnosis; NC turret; Particle swarm optimization; Support vector machine; Time sequence;

D O I：

10.13229/j.cnki.jdxbgxb20211154

中图分类号：

学科分类号：

摘要：

A fault diagnosis method of NC turret based on particle swarm optimization and support vector machine (PSO-SVM) is proposed. Firstly, the NC turret is divided into five subsystems, and a working cycle is divided into four time sequences T1, T2, T3 and T4. Secondly, the feature extraction methods of vibration, motor current, oil pressure and proximity switch signal in different time sequences of NC turret are explored. Finally, fault diagnosis method of NC turret based on PSO-SVM was proposed, and NC turret fault tests were carried out in different time sequences. According to the fault data, support vector machine (SVM) and PSO-SVM fault diagnosis methods are compared and verified. The results show that the fault diagnosis accuracy of T2, T3 and T4 are increased by 28%, 23% and 5%, respectively, which verifies the validity of the proposed fault diagnosis method. The fault diagnosis method proposed in this paper is not only suitable for NC turret, but also provides a new idea for the fault diagnosis of other complex electromechanical system. © 2022, Jilin University Press. All right reserved.

引用

页码：392 / 399

页数：7

共 20 条

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