滚珠丝杠副故障振动信号分析及智能诊断方法综述  

Review of Vibration Signal Analysis and Intelligent Faults Diagnosis Methods for Ball Screw

作　　者：马会杰[1,2,3] 黄志强 邓四二 李开元[2] 鞠飞 MA Huijie;HUANG Zhiqiang;DENG Sier;LI Kaiyuan;JU Fei(Postdoctoral Research Center,Henan University of Science and Technology,Luoyang 471000,China;Postdoctoral Innovation Practice Base,Wuxi Huayang Rolling Bearing Co.,Ltd.,Wuxi 214101,China;College of Automobile and Traffic Engineering,Nanjing Forestry University,Nanjing 210037,China)

机构地区：[1]河南科技大学博士后科研流动站,河南洛阳471000 [2]无锡华洋滚动轴承有限公司博士后创新实践基地,江苏无锡214101 [3]南京林业大学汽车与交通工程学院,南京210037

出　　处：《计算机测量与控制》2025年第1期1-8,28,共9页Computer Measurement &Control

基　　金：河南省博士后科研项目(13554013)。

摘　　要：滚珠丝杠副作为一种旋转运动与直线运动相互转化的高精度部件,被广泛应用在机床、汽车、航空航天等机械设备中,其健康状态对设备的性能和质量具有重大影响;针对滚珠丝杠副振动信号的特点,系统综述了滚珠丝杠副故障振动信号处理及智能诊断方法;介绍了滚珠丝杠副振动信号的特征分析方法,包括时域分析和基展开方法;讨论了滚珠丝杠副智能故障分类方法,包括支持向量机、反向传播神经网络和卷积神经网络等;对当前滚珠丝杠副振动信号处理方法及故障诊断的研究现状进行了总结,并对未来潜在的发展方向进行了展望。Ball screw pairs,serving as high-precision components that converts rotary motion into linear motion and vice versa,are widely used in equipment such as machine tools,automobiles,aerospace,etc,its health status has a significant impact on the performance and quality of equipment.Focusing on the characteristics of the vibration signals of ball screw pairs,this paper summarizes the methods of processing vibration signals and intelligent diagnosis faults for ball screw pairs,and introduces the characteristic analysis methods for the vibration signals of ball screw pairs,including the time-domain analysis and basis expansion methods.The intelligent fault classification methods for the ball screw pairs are discussed,including the support vector machines,backpropagation neural networks,and convolutional neural networks.The current research status on the vibration signal processing methods and fault diagnosis of ball screw pairs is summarized,and the future direction is explored.

关 键 词：滚珠丝杠副 信号分析 故障诊断 人工智能 模式识别 

分 类 号：TP276[自动化与计算机技术—检测技术与自动化装置]