Abstract

This paper addresses an approach for small/minor fault detection of thermocouple sensor in a nuclear power plant. The small/minor fault means the faulty signal does not cross the system threshold values, i.e., the deviation from the normal signal is very less. The faults are detected by extracting the features of sensor signals using symbolic dynamic filter (SDF). A transformation function is proposed that maps the multidimensional heterogeneous sensor signals or trajectories into a homogeneous and approximately unique spectrum space. The transformed trajectories are partitioned by the partition functions and symbol sequences are generated. The probabilistic finite state automata (PFSA) is framed for each trajectory and features of the signals are compactly represented by the probability transition matrix. The faults are detected by analyse the transition matrix. The proposed method is demonstrated by real time data of the fast breeder test reactor (FBTR) with two different case studies.

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