STUDY ON FAULT DIAGNOSIS BASED ON THE QUALITATIVE/QUANTITATIVE MODEL OF SDG AND GENETIC ALGORITHM
(0) In term of multivariate operating conditions, complex dynamic performance and steady qualitative logic relation between variables in power plant thermal process, Signed Directed Graph (SDG) is introduced to apply in fault diagnosis of Power Plant Thermal System. SDG is a self-contained method to effectively diagnosis system failures,which can be constructed effectively by using the grading modeling method aided by simulation technology, but intrinsic limitations restrict it applies in fault diagnosis.Considering the relation among node of SDG can be effective described by constructing a qualitative and quantitative model;PCA that can monitor the correlation among different variables in the system and overcome the shortcoming of single variable analysis in determining the faulty node possibility, the genetic algorithm can be used to search possible fault propagation path quickly, a intelligent fault diagnosis approach is studied in thermal system field. The case studies show the qualitative and quantitative model of SDG has better resolution in fault diagnosis of power plant.
Thermal System SDG PCA Qualitative and Quantitative Model
YONG-GUANG MA JIAN-QIANG GAO LIANG-YU MA QIN YAN PENG TONG
North China Electric Power University, Baoding 071003, China Baoding Technical College of Electric Power, Baoding 071051,China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
2053-2058
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）