{"title":"用于工业燃气轮机内部健康监测的 RVI","authors":"Paul Thompson","doi":"10.32548/2024.me-04450","DOIUrl":null,"url":null,"abstract":"Industrial gas turbines are robust, durable, and dependable, but they can develop problems such as internal wear, loss of thermal barrier coatings, and premature part failures. If left undetected, these issues can lead to significant unplanned costs and downtime. To prevent premature failures, and as an aid in future outage planning, internal health monitoring using remote visual inspection (RVI) can determine whether components are in good condition and fit for service, or if additional repairs are needed. The use of RVI, with a video borescope capable of analyzing and quantifying indications usng 3D data displayed in a point cloud, allows for measuring anomalies with accuracies of 0.001 in. (0.025 mm). In some cases, early detection and 3D analysis of internal issues in industrial gas turbines have saved operators millions of dollars, sometimes even during a single outage.","PeriodicalId":505083,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"RVI For Internal Health Monitoring Of Industrial Gas Turbines\",\"authors\":\"Paul Thompson\",\"doi\":\"10.32548/2024.me-04450\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Industrial gas turbines are robust, durable, and dependable, but they can develop problems such as internal wear, loss of thermal barrier coatings, and premature part failures. If left undetected, these issues can lead to significant unplanned costs and downtime. To prevent premature failures, and as an aid in future outage planning, internal health monitoring using remote visual inspection (RVI) can determine whether components are in good condition and fit for service, or if additional repairs are needed. The use of RVI, with a video borescope capable of analyzing and quantifying indications usng 3D data displayed in a point cloud, allows for measuring anomalies with accuracies of 0.001 in. (0.025 mm). In some cases, early detection and 3D analysis of internal issues in industrial gas turbines have saved operators millions of dollars, sometimes even during a single outage.\",\"PeriodicalId\":505083,\"journal\":{\"name\":\"Materials Evaluation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials Evaluation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32548/2024.me-04450\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Evaluation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32548/2024.me-04450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
RVI For Internal Health Monitoring Of Industrial Gas Turbines
Industrial gas turbines are robust, durable, and dependable, but they can develop problems such as internal wear, loss of thermal barrier coatings, and premature part failures. If left undetected, these issues can lead to significant unplanned costs and downtime. To prevent premature failures, and as an aid in future outage planning, internal health monitoring using remote visual inspection (RVI) can determine whether components are in good condition and fit for service, or if additional repairs are needed. The use of RVI, with a video borescope capable of analyzing and quantifying indications usng 3D data displayed in a point cloud, allows for measuring anomalies with accuracies of 0.001 in. (0.025 mm). In some cases, early detection and 3D analysis of internal issues in industrial gas turbines have saved operators millions of dollars, sometimes even during a single outage.