Title :
Fault diagnosis technology based on the fusion of neural network and fuzzy Logic
Author :
Deng, Na ; Jiang, Chang-sen
Abstract :
Based on localization of single synthetic intelligent fault diagnosis method that applies to construction machinery, Traits of neural network theory and fuzzy Logic method are discussed. A method of the further fusion diagnosis using neural network and fuzzy measurement is proposed. The method uses observational data, integrates diagnosis methods with subjective and impersonal information, which can identify fault more comprehensive and objective, and efficiently improve the fault location capability. This article discusses idea of design, framework and functions, steps of diagnosis. Furthermore, it is proved that the fault diagnosis system is feasible and superior through a real example of combustion system of a certain diesel engine.
Keywords :
combustion; construction equipment; diesel engines; fault location; fuzzy neural nets; fuzzy reasoning; mechanical engineering computing; combustion system; construction machinery; diesel engine; fault identification; fault location capability; fusion diagnosis method; fuzzy Logic method; fuzzy measurement; neural network theory; single synthetic intelligent fault diagnosis method; Biological neural networks; Cognition; Fault diagnosis; Knowledge engineering; Training; D-S evidence theory; further fusion diagnosis; fuzzy logic; neural network prediction;
Conference_Titel :
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4673-0198-5
DOI :
10.1109/ICSAI.2012.6223649