ANALYSIS AND DETECTION OF FAULTS IN A COMBINED CYCLE POWER PLANT

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dc.contributor.authorMALEM Hani
dc.contributor.authorBENLEULMI Hani Abderrahim
dc.contributor.authorDJELLAD Abdelhak (Encadrant)
dc.date.accessioned2025-11-17T13:02:24Z
dc.date.available2025-11-17T13:02:24Z
dc.date.issued2025
dc.description.abstractIn order to improve the performance of industrial processes and prevent efficiency losses caused by technical faults in power plants, it is imperative to have a high-performance monitoring system. There are a lot of methods for diagnosing and detecting faults that have been developed, and in our cas we are using a method that combines two main techniques (coupling diagnosis method), based on wavelet decomposition and Wavelet Energy Entropy (WEE) for feature extraction from sensor signals, and Support Vector Machine (SVM) or Random Forest (RF) for fault classification. This work was implemented by MATLAB software, Wavelet Toolbox for signal decomposition, with Machine Learning Toolbox and TreeBagger for classification.
dc.identifier.urihttp://dspace.ensti-annaba.dz:4000/handle/123456789/912
dc.language.isoen
dc.publisherNational higher scool of technology and engineering-Annaba
dc.titleANALYSIS AND DETECTION OF FAULTS IN A COMBINED CYCLE POWER PLANT
dc.typeThesis
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