电流时域同步平均残差特征统计的滚珠丝杠故障定位方法研究

段洪春; 伍星; 王贵勇; 王东晓; 柳小勤

doi:10.13433/j.cnki.1003-8728.20230282

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电流时域同步平均残差特征统计的滚珠丝杠故障定位方法研究

更新时间：2026-04-23

- 电流时域同步平均残差特征统计的滚珠丝杠故障定位方法研究
- Fault Location Method of Ball Screw for Current Time-domain Synchronous Average Residual Characteristic Statistics
- 机械科学与技术 2025年44卷第7期页码：1221-1227
- 作者机构：
  
  1. 昆明理工大学机构机电工程学院,昆明,650500
  2. 昆明理工大学云南省先进装备智能制造技术重点实验室,昆明,650500
  3. 内蒙古第一机械集团有限公司精密设备维修安装公司,内蒙古,包头,014032
- 作者简介：
  
  [ "段洪春, 硕士研究生," ]
  [ "柳小勤, 教授, 博士," ]
- 基金信息：
  
  国家自然科学基金项目 52265069 云南省重大科技专项计划 202202AC080003
- DOI：10.13433/j.cnki.1003-8728.20230282
  中图分类号：
- 纸质出版：2025
- 稿件说明：
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段洪春, 伍星, 王贵勇, 等. 电流时域同步平均残差特征统计的滚珠丝杠故障定位方法研究[J]. 机械科学与技术, 2025,44(7):1221-1227.

段洪春, 伍星, 王贵勇, et al. Fault Location Method of Ball Screw for Current Time-domain Synchronous Average Residual Characteristic Statistics[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44(7): 1221-1227.
段洪春, 伍星, 王贵勇, 等. 电流时域同步平均残差特征统计的滚珠丝杠故障定位方法研究[J]. 机械科学与技术, 2025,44(7):1221-1227. DOI： 10.13433/j.cnki.1003-8728.20230282.

段洪春, 伍星, 王贵勇, et al. Fault Location Method of Ball Screw for Current Time-domain Synchronous Average Residual Characteristic Statistics[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44(7): 1221-1227. DOI： 10.13433/j.cnki.1003-8728.20230282.

摘要

滚珠丝杠是数控机床的关键传动部件之一，针对其容易出现磨损、点蚀等故障，将导致车床刀具磨损、加工精度降低。因此，提出了一种基于电流时域同步平均残差特征统计的滚珠丝杠故障定位方法，通过采集滚珠丝杠的电机电流信号，利用基于相位的时域同步平均方法，估计确定性信号，通过从原始信号中去除确定性信号来突出残差信号中与故障相关的信号，对残差信号提取特征值，用核偏最小二乘法进行故障检测，对滚珠丝杠进行故障识别和定位。

Abstract

Ball screw is one of the key transmission components of computer numerical control machine tools. In view of its easy to appear wear

pitting and other faults

leading to tool wear and machining accuracy reduction. Therefore

a fault location method of ball screw based on current time-domain synchronous average residual characteristic statistics is proposed

by collecting the motor current signal of ball screw and using time-domain synchronous average method based on phase to estimate deterministic signals. Then the fault-related signals in the residual signals were highlighted by removing the deterministic signals from the original signals. Finally

the characteristic values of the residual signals were extracted

and the fault detection was carried out with the kernel partial least square method. The fault identification and positioning of the ball screw were carried out.

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