Fault detection in Kerman combined cycle power plant boilers by means of support vector machine classifier algorithms and PCA

In this paper, fault detection in HP drum of boilers in Kerman combined cycle power plant is explored by means of support vector machine (SVM) algorithm and principal component analysis (PCA). Initially, SVM classifier algorithm and PCA are discussed and then based on the collecting data on normal and abnormal operating the conditions of boilers, fault detection is carried out via explained methods. Finally, a comparison of these techniques and other routine methods is made to show the superiority with the proposed approaches in Kerman power plant.