Fault Diagnosis System Of The Fire Control System Based On Fuzzy Neural Network

被引：2

作者：

Zhang Peng-jun ^{[1
]}

Bo Yu-cheng ^{[1
]}

Wang Hui-yuan ^{[1
]}

Li Qiang ^{[1
]}

机构：

[1] North Univ China, Mech & Elect Engn Coll, Taiyuan 030051, Shanxi, Peoples R China

来源：

ADVANCED DESIGNS AND RESEARCHES FOR MANUFACTURING, PTS 1-3 | 2013年 / 605-607卷

关键词：

fault diagnosis; neural network; implication operator; fuzzy membership; fire control system;

D O I：

10.4028/www.scientific.net/AMR.605-607.828

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

the paper mainly solves the questions of real time fault detection and diagnosis for fire control system. Function structure and fault characteristics of the fire control system be hierarchical analyzed, through fault omen character and fault reason make up of fault stylebook, use neural network training to improve the fault diagnosis accuracy, select implication operator and calculate the fuzzy membership degree matrix of fault information, through hierarchical reasoning to complete fault recognition and confirm fault source to improve the diagnosis rate. The system is multifunctional which includes of state monitoring, fault diagnosis, diagnosis opinion, the distributed principal and subordinate structure design is propitious to improve reliability and adaptability of the system.

引用

页码：828 / 831

页数：4

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