FUELEX - A KNOWLEDGE-BASED SYSTEM FOR RESEARCH REACTOR FUELING OPERATIONS AND FAULT-DIAGNOSIS

An off-line knowledge based system FUELEX being developed for a 100 MW (thermal) research reactor fueling operations is described. The operational procedure execution of fueling machine, fault diagnosis and trouble shooting have been implemented as three generic tasks in the system. The method of inference used in the system is rule based deduction with priority factor. After identification of lapses or abnormal functioning, the system identifies the procedure to mitigate the consequences of unusual occurrences and assists the operator by confirming the success of the action taken

An operator support system for research reactor operations and fault diagnosis through a connectionist framework and PSA based knowledge based systems

During reactor upset/abnormal conditions, emphasis is placed on the plant operator's ability to quickly identify the problem and perform diagnosis and initiate recovery action to ensure the safety of the plant. However, the reliability of human action is adversely affected at the time of crisis due to time stress and psychological factors. The availability of operational aids capable of monitoring the status of the plant and quickly identifying the deviation from normal operation is expected to significantly improve the operator reliability. The development of operator support systems using probabilistic safety assessment (PSA) techniques and information is finding wide application in nuclear plant operation. Often it is observed that most of the applications use a rule-based approach for diagnosis as well as safety status/transient conditions monitoring. A more efficient approach using artificial neural networks for safety status/transient condition monitoring and rule-based systems for diagnosis and emergency procedure generation has been applied for the development of a prototype operator adviser (OPAD) system for a 100 MW(th) heavy water moderated, cooled and natural uranium fueled research reactor. The development objective of this system is to improve the reliability of operator action and hence the reactor safety at the time of crisis as well as in normal operation. In order to address safety objectives at various stages of development of OPAD, the PSA techniques and tools have been used for knowledge representation. It has been demonstrated, with recall tests on the artificial neural network, that it can efficiently identify the reactor status in real-time scenario. This paper discusses various issues related to the development of an operator support system in a comprehensive way, right from the study of safety objectives, to data collection, to implementation of such a system. (C) 1998 Elsevier Science Limited