Yuanhao Liu, Juan Wang, Yuanchao Liu, X. Yang, Xinpeng Zhu
{"title":"基于BP神经网络算法的结构方程模型在电厂锅炉故障诊断中的应用分析","authors":"Yuanhao Liu, Juan Wang, Yuanchao Liu, X. Yang, Xinpeng Zhu","doi":"10.1109/ICISCAE51034.2020.9236844","DOIUrl":null,"url":null,"abstract":"As the core equipment of combustion, the safe operation of the boiler is of vital importance. Due to the complex structure of the boiler, damage, abrasion, acid gas corrosion and improper operation will all cause faults. In order to effectively avoid faults, a multi-dimensional BP neural network method is used for boiler fault diagnosis modeling, in which the BP neural network adopts multi-dimensional structure, the input layer adopts fuzzy mathematics method to quantify the operation parameters, and a multi-dimensional BP neural network model is established through the correlation between parameters and between parameters and fault types. The experimental results show that the BP neural network fully inherits the advantages of wavelet transform and neural network. The method has good fault diagnosis ability and is obviously superior to wavelet neural network in the accuracy of fault diagnosis.","PeriodicalId":355473,"journal":{"name":"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application Analysis of Structural Equation Model Based on BP Neural Network Algorithm in Fault Diagnosis of Power Plant Boilers\",\"authors\":\"Yuanhao Liu, Juan Wang, Yuanchao Liu, X. Yang, Xinpeng Zhu\",\"doi\":\"10.1109/ICISCAE51034.2020.9236844\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the core equipment of combustion, the safe operation of the boiler is of vital importance. Due to the complex structure of the boiler, damage, abrasion, acid gas corrosion and improper operation will all cause faults. In order to effectively avoid faults, a multi-dimensional BP neural network method is used for boiler fault diagnosis modeling, in which the BP neural network adopts multi-dimensional structure, the input layer adopts fuzzy mathematics method to quantify the operation parameters, and a multi-dimensional BP neural network model is established through the correlation between parameters and between parameters and fault types. The experimental results show that the BP neural network fully inherits the advantages of wavelet transform and neural network. The method has good fault diagnosis ability and is obviously superior to wavelet neural network in the accuracy of fault diagnosis.\",\"PeriodicalId\":355473,\"journal\":{\"name\":\"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCAE51034.2020.9236844\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCAE51034.2020.9236844","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application Analysis of Structural Equation Model Based on BP Neural Network Algorithm in Fault Diagnosis of Power Plant Boilers
As the core equipment of combustion, the safe operation of the boiler is of vital importance. Due to the complex structure of the boiler, damage, abrasion, acid gas corrosion and improper operation will all cause faults. In order to effectively avoid faults, a multi-dimensional BP neural network method is used for boiler fault diagnosis modeling, in which the BP neural network adopts multi-dimensional structure, the input layer adopts fuzzy mathematics method to quantify the operation parameters, and a multi-dimensional BP neural network model is established through the correlation between parameters and between parameters and fault types. The experimental results show that the BP neural network fully inherits the advantages of wavelet transform and neural network. The method has good fault diagnosis ability and is obviously superior to wavelet neural network in the accuracy of fault diagnosis.