{"title":"基于往复式压缩机的故障诊断方法研究","authors":"Guorong Chen, Hong Ren, Yao Liu, Hongli He","doi":"10.1109/IICSPI48186.2019.9096034","DOIUrl":null,"url":null,"abstract":"Based on the research and analysis of related fault diagnosis technologies at home and abroad, a fault diagnosis method for reciprocating compressors based on support vector machine and gravity search algorithm is proposed. This method optimizes the kernel parameters of SVM. Combined with an example of a fault diagnosis model of a reciprocating compressor, the analysis results show that the fault diagnosis method of a reciprocating compressor using the GSA-SVM algorithm has higher recognition accuracy than the SVM algorithm.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Fault Diagnosis Method Based on Reciprocating Compressor\",\"authors\":\"Guorong Chen, Hong Ren, Yao Liu, Hongli He\",\"doi\":\"10.1109/IICSPI48186.2019.9096034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the research and analysis of related fault diagnosis technologies at home and abroad, a fault diagnosis method for reciprocating compressors based on support vector machine and gravity search algorithm is proposed. This method optimizes the kernel parameters of SVM. Combined with an example of a fault diagnosis model of a reciprocating compressor, the analysis results show that the fault diagnosis method of a reciprocating compressor using the GSA-SVM algorithm has higher recognition accuracy than the SVM algorithm.\",\"PeriodicalId\":318693,\"journal\":{\"name\":\"2019 2nd International Conference on Safety Produce Informatization (IICSPI)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 2nd International Conference on Safety Produce Informatization (IICSPI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IICSPI48186.2019.9096034\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IICSPI48186.2019.9096034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Fault Diagnosis Method Based on Reciprocating Compressor
Based on the research and analysis of related fault diagnosis technologies at home and abroad, a fault diagnosis method for reciprocating compressors based on support vector machine and gravity search algorithm is proposed. This method optimizes the kernel parameters of SVM. Combined with an example of a fault diagnosis model of a reciprocating compressor, the analysis results show that the fault diagnosis method of a reciprocating compressor using the GSA-SVM algorithm has higher recognition accuracy than the SVM algorithm.