Expert Alarm System for Prediction of Chemistry Faults in a Power Station
The integration of rule based techniques in traditional real-time systems is a promising approach to cope with the growing complexity of real-world applications. Real-time expert systems are on-line knowledge-based systems that combine analytical process models with conventional process control to monitor complex industrial processes and to assist in problem identification. Intelligent system for alarm diagnosis and root cause analysis and operator guidance in process plants is an important area for which the real time expert system is being used. Fault monitoring and prediction is of prime importance in a Power Plant. This paper proposes an expert system to aid plant operation engineers in diagnosing the cause of abnormal water / steam parameters in a Fossil fuel Power station. The diagnostic decisions are written in the form of fault trees. Fault trees fare developed or all steam water cycle parameters. This system enables the operator to take preventive measures in time, avoiding costly outages, in turn increasing the plant availability and efficiency. The proposed system has been successfully implemented in a thermal power plant on PI Process book environment of OSI soft and is written in Microsoft Visual Basic.
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