基于两级信号融合和深度多尺度多传感器网络的滚动轴承故障诊断。

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2024-11-01 DOI:10.1016/j.isatra.2024.08.033
Zuozhou Pan , Yang Guan , Fengjie Fan , Yuanjin Zheng , Zhiping Lin , Zong Meng
{"title":"基于两级信号融合和深度多尺度多传感器网络的滚动轴承故障诊断。","authors":"Zuozhou Pan ,&nbsp;Yang Guan ,&nbsp;Fengjie Fan ,&nbsp;Yuanjin Zheng ,&nbsp;Zhiping Lin ,&nbsp;Zong Meng","doi":"10.1016/j.isatra.2024.08.033","DOIUrl":null,"url":null,"abstract":"<div><div>In order to realize high-precision diagnosis of bearings faults in a multi-sensor detection environment, a fault diagnosis method based on two-stage signal fusion and deep multi-scale multi-sensor networks is proposed. Firstly, the signals are decomposed and fused using weighted empirical wavelet transform to enhance weak features and reduce noise. Secondly, an improved random weighting algorithm is proposed to perform a second weighted fusion of the signals to reduce the total mean square error. The fused signals are input into the deep multi-scale residual network, the feature information of different convolutional layers is extracted through dilated convolution, and the features are fused using pyramid theory. Finally, the bearings states are classified according to the fusion features. Experiment results show the effectiveness and superiority of this method.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"154 ","pages":"Pages 311-334"},"PeriodicalIF":6.3000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rolling bearings fault diagnosis based on two-stage signal fusion and deep multi-scale multi-sensor network\",\"authors\":\"Zuozhou Pan ,&nbsp;Yang Guan ,&nbsp;Fengjie Fan ,&nbsp;Yuanjin Zheng ,&nbsp;Zhiping Lin ,&nbsp;Zong Meng\",\"doi\":\"10.1016/j.isatra.2024.08.033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In order to realize high-precision diagnosis of bearings faults in a multi-sensor detection environment, a fault diagnosis method based on two-stage signal fusion and deep multi-scale multi-sensor networks is proposed. Firstly, the signals are decomposed and fused using weighted empirical wavelet transform to enhance weak features and reduce noise. Secondly, an improved random weighting algorithm is proposed to perform a second weighted fusion of the signals to reduce the total mean square error. The fused signals are input into the deep multi-scale residual network, the feature information of different convolutional layers is extracted through dilated convolution, and the features are fused using pyramid theory. Finally, the bearings states are classified according to the fusion features. Experiment results show the effectiveness and superiority of this method.</div></div>\",\"PeriodicalId\":14660,\"journal\":{\"name\":\"ISA transactions\",\"volume\":\"154 \",\"pages\":\"Pages 311-334\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISA transactions\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0019057824004142\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISA transactions","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0019057824004142","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

为了在多传感器检测环境下实现轴承故障的高精度诊断,提出了一种基于两阶段信号融合和深度多尺度多传感器网络的故障诊断方法。首先,利用加权经验小波变换对信号进行分解和融合,以增强弱特征并降低噪声。其次,提出一种改进的随机加权算法,对信号进行第二次加权融合,以减少总均方误差。融合后的信号输入深度多尺度残差网络,通过扩张卷积提取不同卷积层的特征信息,并利用金字塔理论对特征进行融合。最后,根据融合特征对轴承状态进行分类。实验结果表明了这种方法的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Rolling bearings fault diagnosis based on two-stage signal fusion and deep multi-scale multi-sensor network
In order to realize high-precision diagnosis of bearings faults in a multi-sensor detection environment, a fault diagnosis method based on two-stage signal fusion and deep multi-scale multi-sensor networks is proposed. Firstly, the signals are decomposed and fused using weighted empirical wavelet transform to enhance weak features and reduce noise. Secondly, an improved random weighting algorithm is proposed to perform a second weighted fusion of the signals to reduce the total mean square error. The fused signals are input into the deep multi-scale residual network, the feature information of different convolutional layers is extracted through dilated convolution, and the features are fused using pyramid theory. Finally, the bearings states are classified according to the fusion features. Experiment results show the effectiveness and superiority of this method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
期刊最新文献
Editorial Board ROM-based stochastic optimization for a continuous manufacturing process Multiscale dynamically parallel shrinkage network for fault diagnosis of aviation hydraulic pump and its generalizable applications Uncertainty propagation from probe spacing to Fourier 3-probe straightness measurement Event-triggered adaptive neural prescribed performance admittance control for constrained robotic systems without velocity measurements
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1