Key Words: Case-Base Reasoning; Risk Management; Fault Tree; System Control; Power Plant.
Abstract. The management of Energy Power Plants (PP) is a multifaceted technological process influenced by various factors, including environmental changes, the state of system control elements, and potential faults in sensors and other critical components. During the control of Power Plants, some failures in system devices (such as sensors, valves, and other essential components) can occur. These failures can lead to damage and malfunctions within the system control loops, ultimately causing the system to work unstably and rise risk situations. Early diagnosis and prediction of these failures are crucial for maintaining the safe and efficient operation of Energy Power Plants. The research introduces a new approach for diagnosing the state of the system and presents a mechanism for predicting some failures of control loop elements at an early stage. The proposed approach combines Fault Tree (FT) analysis with Case-Based Reasoning (CBR) in a way to provide a comprehensive system for prediction of fault devices detection. Using the previous knowledge for the technological characteristics of control devices elements – such as material wear, working time under high load, and contamination of sensors and photocells is used for forming of knowledge base-oriented system (CBR).
