基于PSO-SVM及时序环节的数控刀架故障诊断方法  

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

作　　者：罗巍[1,2] 卢博 陈菲 马腾 LUO Wei;LU Bo;CHEN Fei;MA Teng(Key Laboratory of CNC Equipment Reliability,Ministry of Education,Jilin University,Changchun 130022,China;College of Mechanical and Aerospace Engineering,Jilin University,Changchun 130022,China;Changchun Equipment&Technology Research Institute,Changchun 130012,China;Sino-German College of Intelligent Manufacturing,Shenzhen Technology University,Shenzhen 518118,China)

机构地区：[1]吉林大学数控装备可靠性教育部重点实验室,长春130022 [2]吉林大学机械与航空航天工程学院,长春130022 [3]长春设备工艺研究所,长春130012 [4]深圳技术大学中德智能制造学院,深圳518118

出　　处：《吉林大学学报（工学版）》2022年第2期392-399,共8页Journal of Jilin University:Engineering and Technology Edition

基　　金：吉林省教育厅项目(JJKH20211068KJ).

摘　　要：提出了一种基于粒子群-支持向量机(PSO-SVM)及时序环节的数控刀架故障诊断方法。首先,将数控刀架划分为5个子系统,并将一个工作周期划分为4个时序环节(T1、T2、T3、T4);其次,探索了数控刀架不同时序环节振动、电机电流、油压以及接近开关等信号的特征提取方法;最后,提出了基于PSO-SVM的数控刀架故障诊断方法,并开展了不同时序环节的数控刀架故障试验。根据故障数据对支持向量机(SVM)和PSO-SVM两种故障诊断方法进行了对比验证。结果表明:时序环节T2、T3和T4的故障诊断准确率分别提高了28%、23%和5%,验证了该故障诊断方法的有效性。本文方法不仅适用于数控刀架,还为其他复杂机电系统的故障诊断研究提供了一个新思路。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.

关 键 词：数控刀架 支持向量机 粒子群算法 时序环节 故障诊断 

分 类 号：TH133.33[机械工程—机械制造及自动化] TP183[自动化与计算机技术—控制理论与控制工程]