IFDD: Intelligent Fault Detection and Diagnosis-Application to a Cogeneration and Cooling Plant

Power producing plants possess a maintenance cost of about 30% of the total power generating cost. Studies also show that a cost reduction of about 30% can be achieved by shifting from preventive maintenance to condition based maintenance. This study presents an intelligent fault detection and diagnosis system designed for a cogeneration and cooling plant. Fuzzy systems are used to address multiple operating regions, nonlinear model identification and fault diagnosis. Performance of the designed system is demonstrated by conducting case studies on actual Gas Turbine Generator (GTG), Heat Recovery Steam Generator (HRSG) and steam absorption chiller. In most of the tested cases, the system was found capable of providing 95 to 100% true detection and true diagnosis, respectively. For assumed incipient faults, it was found performing better than principal component analysis or auto-associative neural networks. While having a dedicated graphical user interface, it is also designed to be applicable for steady state simulation of the GTG and HRSG, respectively.