An intelligent diagnosis model of accidents in nuclear power plant

Abstract

This essay focus on the situation when the operator of the main control room can not handle the accident in time or make wrong judgment under accident condition in nuclear power plant, which may lead to the occurrence of major accidents or even more accidents concurrently. An intelligent fuzzy diagnosis model based on Grey Relational degree is constructed in this paper, by establishing accident-state correlation matrix and accident-state probability matrix, defining the vector of information weights for accident characteristic vector and monitoring result vector with linear transform, using Grey Relation to measure the relevance degree between monitoring result vector and accident characteristic vector, Searching for suspected accidents approaching to real solutions in iterative recursive algorithms, realizing automatic fuzzy diagnosis of multiple accidents. The results of simulation experiments of LOCA accidents indicate that the model and algorithm can diagnose various common accidents accurately and rapidly in complex nuclear power systems, providing strategy for operator’s diagnosis decision.