基于模糊支持向量机的汽车发动机故障智能诊断技术

M. Weng
{"title":"基于模糊支持向量机的汽车发动机故障智能诊断技术","authors":"M. Weng","doi":"10.1109/APWCS.2010.17","DOIUrl":null,"url":null,"abstract":"The fault reasoning and diagnosis are carried out by means of analysis on the contents of CO, HC, CO2 and O2 in the exhaust gas discharged from gasoline engine. The support vector machine is applied to fault diagnosis of the exhaust gas discharged from gasoline engine. Taken the fault data recorded the exhaust gas discharged from gasoline engine as the sample sets, part of the fault data of the exhaust gas is studied, by use of classification machine. The calculation results show that the average accuracy of the fault diagnosis could reach about 95% with fuzzy support vector machine.","PeriodicalId":354322,"journal":{"name":"2010 Asia-Pacific Conference on Wearable Computing Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Intelligent Diagnosis Techniques in Automotive Engines Fault Based on Fuzzy Support Vector Machine\",\"authors\":\"M. Weng\",\"doi\":\"10.1109/APWCS.2010.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The fault reasoning and diagnosis are carried out by means of analysis on the contents of CO, HC, CO2 and O2 in the exhaust gas discharged from gasoline engine. The support vector machine is applied to fault diagnosis of the exhaust gas discharged from gasoline engine. Taken the fault data recorded the exhaust gas discharged from gasoline engine as the sample sets, part of the fault data of the exhaust gas is studied, by use of classification machine. The calculation results show that the average accuracy of the fault diagnosis could reach about 95% with fuzzy support vector machine.\",\"PeriodicalId\":354322,\"journal\":{\"name\":\"2010 Asia-Pacific Conference on Wearable Computing Systems\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Asia-Pacific Conference on Wearable Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APWCS.2010.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Asia-Pacific Conference on Wearable Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APWCS.2010.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

通过对汽油机排放废气中CO、HC、CO2和O2含量的分析,进行故障推理和诊断。将支持向量机应用于汽油机废气的故障诊断。以记录汽油机排气的故障数据为样本集,利用分类机对部分排气故障数据进行了研究。计算结果表明,采用模糊支持向量机进行故障诊断的平均准确率可达95%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Diagnosis Techniques in Automotive Engines Fault Based on Fuzzy Support Vector Machine
The fault reasoning and diagnosis are carried out by means of analysis on the contents of CO, HC, CO2 and O2 in the exhaust gas discharged from gasoline engine. The support vector machine is applied to fault diagnosis of the exhaust gas discharged from gasoline engine. Taken the fault data recorded the exhaust gas discharged from gasoline engine as the sample sets, part of the fault data of the exhaust gas is studied, by use of classification machine. The calculation results show that the average accuracy of the fault diagnosis could reach about 95% with fuzzy support vector machine.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信