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As an important gas path performance parameter of gas turbine, exhaust gas temperature (EGT) can represent the thermal health condition of gas turbine. In order to monitor and diagnose the EGT effectively, a fusion approach based on fuzzy C-means (FCM) clustering algorithm and support vector machine (SVM) classification model is proposed in this paper. Considering the distribution characteristics of gas turbine EGT, FCM clustering algorithm is used to realize clustering analysis and obtain thedoi:10.1155/2015/240267 fatcat:d6tuj3txrbaydmqqjoqan7hvo4