{"title":"轴向液压柱塞泵计算机辅助智能故障诊断方法","authors":"Yi-Hui Chen Yi-Hui Chen","doi":"10.53106/199115992023043402018","DOIUrl":null,"url":null,"abstract":"\n Axial hydraulic piston pump is widely used in industrial production due to its high pressure resistance and large displacement characteristics, but high pressure and large displacement are also the main causes of piston pump failure. Starting from the fault mechanism of the axial hydraulic piston pump, this paper analyzes and studies the signal characteristics of the fault, and establishes the fault signal acquisition and analysis model. Finally, it discusses the construction of the diagnosis system from both hardware and software, so that the processed typical fault signals can be sent into the intelligent diagnosis system to determine the fault type. Finally, the method in this paper is verified by experiments, which proves the reliability and effectiveness of the diagnosis system.\n \n","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Computer-Aided Intelligent Fault Diagnosis Method for Axial Hydraulic Piston Pump\",\"authors\":\"Yi-Hui Chen Yi-Hui Chen\",\"doi\":\"10.53106/199115992023043402018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Axial hydraulic piston pump is widely used in industrial production due to its high pressure resistance and large displacement characteristics, but high pressure and large displacement are also the main causes of piston pump failure. Starting from the fault mechanism of the axial hydraulic piston pump, this paper analyzes and studies the signal characteristics of the fault, and establishes the fault signal acquisition and analysis model. Finally, it discusses the construction of the diagnosis system from both hardware and software, so that the processed typical fault signals can be sent into the intelligent diagnosis system to determine the fault type. Finally, the method in this paper is verified by experiments, which proves the reliability and effectiveness of the diagnosis system.\\n \\n\",\"PeriodicalId\":345067,\"journal\":{\"name\":\"電腦學刊\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"電腦學刊\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53106/199115992023043402018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"電腦學刊","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53106/199115992023043402018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Computer-Aided Intelligent Fault Diagnosis Method for Axial Hydraulic Piston Pump
Axial hydraulic piston pump is widely used in industrial production due to its high pressure resistance and large displacement characteristics, but high pressure and large displacement are also the main causes of piston pump failure. Starting from the fault mechanism of the axial hydraulic piston pump, this paper analyzes and studies the signal characteristics of the fault, and establishes the fault signal acquisition and analysis model. Finally, it discusses the construction of the diagnosis system from both hardware and software, so that the processed typical fault signals can be sent into the intelligent diagnosis system to determine the fault type. Finally, the method in this paper is verified by experiments, which proves the reliability and effectiveness of the diagnosis system.