Fault Diagnosis of Car Engine by Using a Novel GA-Based Extension Recognition Method | Zendy

Menghui Wang | Zendy; PiChu Wu | Zendy

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Fault Diagnosis of Car Engine by Using a Novel GA-Based Extension Recognition Method

Author(s) -

Menghui Wang,

PiChu Wu

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/735485

Subject(s) - fault (geology) , extension (predicate logic) , reliability (semiconductor) , engineering , automotive engine , genetic algorithm , automotive engineering , pattern recognition (psychology) , computer science , artificial intelligence , machine learning , power (physics) , physics , quantum mechanics , seismology , programming language , geology

Due to the passenger’s security, the recognized hidden faults in car engines are the most important work for a maintenance engineer, so they can regulate the engines to be safe and improve the reliability of automobile systems. In this paper, we will present a novel fault recognition method based on the genetic algorithm (GA) and the extension theory and also apply this method to the fault recognition of a practical car engine. The proposed recognition method has been tested on the Nissan Cefiro 2.0 engine and has also been compared to other traditional classification methods. Experimental results are of great effect regarding the hidden fault recognition of car engines, and the proposed method can also be applied to other industrial apparatus.

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