典型文献
A Fault Diagnosis Model for Complex Industrial Process Based on Improved TCN and 1D CNN
文献摘要：
Fast and accurate fault diagnosis of strongly coupled,time-varying,multivariable complex industrial processes remain a challenging problem.We propose an industrial fault diagnosis model.This model is established on the base of the temporal con-volutional network(TCN)and the one-dimensional convolutional neural network(1DCNN).We add a batch normalization layer be-fore the TCN layer,and the activation function of TCN is replaced from the initial ReLU function to the LeakyReLU function.To ex-tract local correlations of features,a 1D convolution layer is added after the TCN layer,followed by the multi-head self-attention mechanism before the fully connected layer to enhance the model's diagnostic ability.The extended Tennessee Eastman Process(TEP)dataset is used as the index to evaluate the perfor-mance of our model.The experiment results show the high fault recognition accuracy and better generalization performance of our model,which proves its effectiveness.Additionally,the model's application on the diesel engine failure dataset of our partner's proiect validates the effectiveness of it in industrial scenarios.
文献关键词：
中图分类号：
作者姓名：
WANG Mingsheng;HUANG Bo;HE Chuanpeng;Li Peipei;ZHANG Jiahao;CHEN Yu;TONG Jie
作者机构：
School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201600,China;State Grid Shanghai Municipal Electric Power Company,Shanghai 200122,China;CSG Smart Science&Technology Co.,LTD.,Shanghai 201203,China
文献出处：
引用格式：
[1]WANG Mingsheng;HUANG Bo;HE Chuanpeng;Li Peipei;ZHANG Jiahao;CHEN Yu;TONG Jie-.A Fault Diagnosis Model for Complex Industrial Process Based on Improved TCN and 1D CNN)[J].武汉大学自然科学学报（英文版）,2022(06):453-464
A类：
proiect
B类：
Fault,Diagnosis,Model,Complex,Industrial,Process,Based,Improved,TCN,Fast,accurate,fault,diagnosis,strongly,coupled,varying,multivariable,complex,industrial,processes,remain,challenging,problem,We,propose,model,This,established,base,temporal,network,one,dimensional,convolutional,neural,1DCNN,batch,normalization,layer,activation,function,replaced,from,initial,LeakyReLU,To,tract,local,correlations,features,added,after,followed,by,head,self,attention,mechanism,before,fully,connected,enhance,diagnostic,ability,extended,Tennessee,Eastman,TEP,dataset,used,evaluate,our,experiment,results,show,high,recognition,accuracy,better,generalization,performance,which,proves,its,effectiveness,Additionally,application,diesel,engine,failure,partner,validates,scenarios
AB值：
0.581832
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