机床与液压2024,Vol.52Issue(4) :200-205.DOI:10.3969/j.issn.1001-3881.2024.04.031

基于两种改进RedNet的滚动轴承故障诊断方法研究

Research on the Rolling Bearing Fault Diagnosis Based on Two Improved RedNet

郑直 单思然 曾魁魁 王志军 朱勇
机床与液压2024,Vol.52Issue(4) :200-205.DOI:10.3969/j.issn.1001-3881.2024.04.031

基于两种改进RedNet的滚动轴承故障诊断方法研究

Research on the Rolling Bearing Fault Diagnosis Based on Two Improved RedNet

郑直 1单思然 1曾魁魁 1王志军 1朱勇2
扫码查看

作者信息

  • 1. 华北理工大学机械工程学院,河北唐山 063210
  • 2. 江苏大学国家水泵及系统工程技术研究中心,江苏镇江 212013
  • 折叠

摘要

RedNet网络自带的余弦退火算法易使学习率陷入局部极小值,出现拟合现象,导致精度过低.针对此问题,对RedNet进行改进处理,提出了两种MicroNet-RedNet和MobileNetV3-RedNet新型网络.基于RedNet的Involution核思想,用MicroNet网络的微分解卷积和Dynamic Shift-Max动态激活函数对RedNet网络进行改进处理,提出了 MicroNet-RedNet新型网络;利用MobileNetV3网络的h-swish激活函数和Squeeze-and-Excitation模块对RedNet进行改进处理,提出Mobile-NetV3-RedNet新型网络.通过对滚动轴承的实测内圈、外圈和滚动体3种故障的诊断分析可知:所提MicroNet-RedNet和所提MobileNetV3-RedNet可有效地诊断上述故障,诊断精度分别高达98.57%和93.81%,且较传统CNN和原算法RedNet的诊断精度提高很多.

Abstract

The cosine annealing algorithm of RedNet network is easy to make the learning rate fall into the local minimum and the over-fitting phenomenon occurs,which leads to the low accuracy.In view of the problems,RedNet was improved and two new networks of MicroNet-RedNet and MobileNetV3-RedNet were proposed.Based on the Involution kernel idea of RedNet,the micro-factorized con-volution and Dynamic Shift-Max activation function of MicroNet were used to improve RedNet,and thus a new network MicroNet-Red-Net was proposed.The h-swish activation function and Squeeze-and-Excitation module of MobileNetV3 were applied to improve Red-Net,and thus a new network MobileNetV3-RedNet was proposed.Based on the measured inner ring fault,outer ring fault and rolling ele-ment fault of the rolling bearing,it can be seen that the above faults can be diagnosed by the two proposed networks of MicroNet-Red-Net and MobileNetV3-RedNet effectively.The accuracies are as high as 98.57%and 93.81%respectively,which are much higher than those got by traditional CNN and the original RedNet.

关键词

滚动轴承/RedNet网络/MicroNet网络/MobileNetV3网络

Key words

rolling bearing/RedNet/MicroNet/MobileNetV3

引用本文复制引用

基金项目

河北省自然科学基金(E2022209086)

河北省高层次人才项目(B2020003033)

唐山市科技创新团队培养计划(21130208D)

河北省科技重大专项(22282203Z)

出版年

2024
机床与液压
中国机械工程学会 广州机械科学研究院有限公司

机床与液压

CSTPCD北大核心
影响因子:0.32
ISSN:1001-3881
参考文献量17
段落导航相关论文