中国造纸学报2025，Vol.40Issue(1)：179-190,12.DOI:10.11981/j.issn.1000-6842.2025.01.179
小样本下基于并行异构网络的变工况纸机轴承故障诊断方法
Fault Diagnosis Method of Paper Machine Bearings for Variable Working Conditions Based on Parallel Heterogeneous Network in Small Samples
摘要
Abstract
In practical applications,the traditional paper machine bearing fault diagnosis model has problems,such as decreased accuracy in fault diagnosis under variable working conditions due to the small amount of fault vibration signal data and low proportion of effective signal in-formation.In response to this issue,this project proposed a fault diagnosis method of paper machine bearings for variable working conditions based on parallel heterogeneous network in small samples.Firstly,the source and target domain signals were converted into corresponding Gram angle field matrix,Markov transition field matrix,and Euclidean distance matrix,respectively.The obtained three matrices were cross combined row by row and used as network inputs.Secondly,based on convolutional neural network(CNN),2D-CNN was improved by de-signing a multi-channel parallel heterogeneous network that integrated attention mechanism to automatically extract deep features of signals.Then,based on adversarial thinking,domain discriminators and classifiers were designed to align the feature edge distributions of the two do-mains through multi kernel maximum mean difference(MK-MMD),achieving recognition of bearing faults under variable operating condi-tions.Finally,transfer learning experiments were conducted to verify the data collected from the Case Western Reserve University rolling bearing dataset,and the laboratory self-built paper machine bearing fault simulation platform.The results indicated that the paper machine bearing fault transfer learning network model had excellent feature mining ability and high recognition accuracy for paper machine bearing faults under variable operating conditions.关键词
并行异构CNN/纸机轴承/轴承故障诊断Key words
parallel heterogeneous CNN/paper machine bearings/bearing fault diagnosis分类
轻工纺织引用本文复制引用
汤伟,杨亦君,王孟效,刘英伟..小样本下基于并行异构网络的变工况纸机轴承故障诊断方法[J].中国造纸学报,2025,40(1):179-190,12.基金项目
国家自然科学基金(62073206) （62073206）
陕西省技术创新引导专项(2023GXLH-071). （2023GXLH-071）
