{"title":"基于Android平台的热成像状态监测","authors":"N. Verma, Rishabh Singh, Sonal Dixit, A. Salour","doi":"10.1109/IBSS.2015.7456638","DOIUrl":null,"url":null,"abstract":"The use of thermal images for condition based monitoring is becoming very popular in industries. This paper presents a simple approach for condition based monitoring of machines using thermal Images on Android Platform. This approach is non-contact, fast and precise for CBM of rotating and non-rotating machines. The proposed approach has been successfully implemented on Android smartphone for CBM of prototype machine. The application uses standard OpenCV library functions to implement processing logic. For this the temperature profile of overall machine from different views was captured and analyzed using thermal images. Regression model was developed to find relation between local temperature and pixel intensity which helped in recognizing the condition of prototype machine.","PeriodicalId":317804,"journal":{"name":"2015 IEEE Bombay Section Symposium (IBSS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Thermal imaging based condition based monitoring on Android platform\",\"authors\":\"N. Verma, Rishabh Singh, Sonal Dixit, A. Salour\",\"doi\":\"10.1109/IBSS.2015.7456638\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of thermal images for condition based monitoring is becoming very popular in industries. This paper presents a simple approach for condition based monitoring of machines using thermal Images on Android Platform. This approach is non-contact, fast and precise for CBM of rotating and non-rotating machines. The proposed approach has been successfully implemented on Android smartphone for CBM of prototype machine. The application uses standard OpenCV library functions to implement processing logic. For this the temperature profile of overall machine from different views was captured and analyzed using thermal images. Regression model was developed to find relation between local temperature and pixel intensity which helped in recognizing the condition of prototype machine.\",\"PeriodicalId\":317804,\"journal\":{\"name\":\"2015 IEEE Bombay Section Symposium (IBSS)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Bombay Section Symposium (IBSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IBSS.2015.7456638\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Bombay Section Symposium (IBSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IBSS.2015.7456638","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thermal imaging based condition based monitoring on Android platform
The use of thermal images for condition based monitoring is becoming very popular in industries. This paper presents a simple approach for condition based monitoring of machines using thermal Images on Android Platform. This approach is non-contact, fast and precise for CBM of rotating and non-rotating machines. The proposed approach has been successfully implemented on Android smartphone for CBM of prototype machine. The application uses standard OpenCV library functions to implement processing logic. For this the temperature profile of overall machine from different views was captured and analyzed using thermal images. Regression model was developed to find relation between local temperature and pixel intensity which helped in recognizing the condition of prototype machine.