{"title":"Data-Driven Model Selection Study for Long-Term Performance Deterioration of Gas Turbines","authors":"Yuan Liu, A. Banerjee, Houman Hanachi, Amar Kumar","doi":"10.1109/ICPHM.2019.8819433","DOIUrl":null,"url":null,"abstract":"Performance of gas turbine engine (GTE) deteriorates with structural aging. The availability of operating data from GTE and capability to perform data analysis, provides an opportunity to identify long-term performance deterioration and relate to more difficult to detect structural degradation. In this work, performance analysis of a low power rating and partially loaded industrial GTE was carried out by using a model-free data analytic approach. A performance index (ratio of power generation to fuel consumption) is proposed as the metrics for monitoring the engine performance, and monitor the long-term degradation symptom. A comparative model selection study has been conducted among three multivariable models to select the best model describing long-term performance deterioration of the GTE.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":" October","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPHM.2019.8819433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Performance of gas turbine engine (GTE) deteriorates with structural aging. The availability of operating data from GTE and capability to perform data analysis, provides an opportunity to identify long-term performance deterioration and relate to more difficult to detect structural degradation. In this work, performance analysis of a low power rating and partially loaded industrial GTE was carried out by using a model-free data analytic approach. A performance index (ratio of power generation to fuel consumption) is proposed as the metrics for monitoring the engine performance, and monitor the long-term degradation symptom. A comparative model selection study has been conducted among three multivariable models to select the best model describing long-term performance deterioration of the GTE.