Advances in Fault Detection and Diagnosis for Thermal Power Plants: A Review of Intelligent Techniques

Thermal power plants (TPPs) are critical to supplying energy society, and ensuring their safe efficient operation is a top priority. To minimize maintenance shutdowns costs, modern TPPs have adopted advanced fault detection diagnosis (FDD) techniques. These FDD approaches can be divided into three main categories: model-based, data-driven-based, statistical-based methods. Despite the practical limitations of model-based methods, multitude data-driven statistical techniques been developed monitor key equipment in TPPs. The contribution this paper systematic review methods that addresses literature gap by providing comprehensive comparison analysis these discusses most relevant strategies, including data-driven, approaches, applications enhancing efficiency reliability Our highlights novel innovative aspects emphasizes significance sustainable development long-term viability thermal generation. This further explores recent advancements intelligent for boilers turbines It also real-world applications, analyzes challenges current approaches. need research field, outlines potential future directions improve safety, efficiency, Overall, provides valuable insights state-of-the-art TPPs, serves as guide development.