{"title":"人工蚂蚁在感应电机状态监测中的专用应用","authors":"A. Soualhi, H. Razik, G. Clerc","doi":"10.1109/DEMPED.2013.6645769","DOIUrl":null,"url":null,"abstract":"In the last decade, the field of diagnosis has attracted the attention of many researchers, especially for the detection of faults in induction motors. The condition monitoring of induction motors is generally based on the analysis of signals coming from one or several sensors. This analysis is performed by the motor current signature analysis (MCSA) which is considered as the most popular fault detection technique. This approach considers that a failed component generates a frequency in the motor current spectrum and measuring the amplitude of this frequency can help us to identify and quantify the fault severity. So, the frequency amplitude of the faulty component has to be known. This paper suggests the use of a heuristic technique inspired by the behavior of a colony of ants to track these frequencies. This technique is very easy to implement and converge quickly to a solution. The proposed technique is described and the experimental results illustrate this novel technique.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A dedicated Application of artificial ants for the condition monitoring of induction motors\",\"authors\":\"A. Soualhi, H. Razik, G. Clerc\",\"doi\":\"10.1109/DEMPED.2013.6645769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the last decade, the field of diagnosis has attracted the attention of many researchers, especially for the detection of faults in induction motors. The condition monitoring of induction motors is generally based on the analysis of signals coming from one or several sensors. This analysis is performed by the motor current signature analysis (MCSA) which is considered as the most popular fault detection technique. This approach considers that a failed component generates a frequency in the motor current spectrum and measuring the amplitude of this frequency can help us to identify and quantify the fault severity. So, the frequency amplitude of the faulty component has to be known. This paper suggests the use of a heuristic technique inspired by the behavior of a colony of ants to track these frequencies. This technique is very easy to implement and converge quickly to a solution. The proposed technique is described and the experimental results illustrate this novel technique.\",\"PeriodicalId\":425644,\"journal\":{\"name\":\"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DEMPED.2013.6645769\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEMPED.2013.6645769","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A dedicated Application of artificial ants for the condition monitoring of induction motors
In the last decade, the field of diagnosis has attracted the attention of many researchers, especially for the detection of faults in induction motors. The condition monitoring of induction motors is generally based on the analysis of signals coming from one or several sensors. This analysis is performed by the motor current signature analysis (MCSA) which is considered as the most popular fault detection technique. This approach considers that a failed component generates a frequency in the motor current spectrum and measuring the amplitude of this frequency can help us to identify and quantify the fault severity. So, the frequency amplitude of the faulty component has to be known. This paper suggests the use of a heuristic technique inspired by the behavior of a colony of ants to track these frequencies. This technique is very easy to implement and converge quickly to a solution. The proposed technique is described and the experimental results illustrate this novel technique.