JK0360219 / JKNS / 논문
Vol. 36, No. 3, Page 219 (10 pgs.), Year 2004-06
Title:	Study on the Self Diagnostic Monitoring System for an Air-Operated Valve : Algorithm for Diagnosing Defects
Author(s) :	Kim Wooshik, Chai Jangbom, Choi Hyunwoo,
File :	JK0360219.pdf
Abstract
[1] and [2] present an approach to diagnosing possible defects in the mechanical systems of a nuclear power plant. In this paper, by using a fault library as a database and training data, we develop a diagnostic algorithm 1) to decide whether an Air Operated Valve system is sound or not and 2) to identify the defect from which an Air-Operated Valve system suffers, if any. This algorithm is composed of three stages: a neural net stage, a non-neural net stage, and an integration stage. The neural net stage is a simple perceptron, a pattern-recognition module, using a neural net. The non-neural net stage is a simple pattern-matching algorithm, which translates the degree of matching into a corresponding number. The integration stage collects each output and makes a decision. We present a simulation result and confirm that the developed algorithm works accurately, if the input matches one in the database.
Keywords :	AOV; symptom; neural net; pattern recognition; pattern matching