BibTeX
@MISC{Chen_diagnosisbased,
author = {Peijiang Chen},
title = {DIAGNOSIS BASED ON NEURAL NETWORK 1},
year = {}
}
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Abstract
Because of the product variety and structure complexity of the engineering machinery, it was difficult to meet the requirements of fault detection and maintenance for the traditional diagnosis technologies. In order to improve the diagnostic level, the intelligent control technology of neural network and its application in engineering machinery fault diagnosis were studied. The basic concepts of engineering machinery fault diagnosis were introduced and several commonly used fault diagnosis methods were discussed. On the basis of analyzing the model and algorithm of BP neural network, a fault diagnosis system of roller’s electrical system was designed and implemented based on neural network. The experimental result showed that the sample output corresponded to the expected output, it was reliable and the requirement of fault diagnosis was achieved. The system had certain practical value in realizing intelligent fault diagnosis for engineering machinery.
Keyphrases
diagnosis based neural network engineering machinery fault diagnosis engineering machinery neural network diagnostic level intelligent control technology certain practical value basic concept structure complexity traditional diagnosis technology intelligent fault diagnosis fault diagnosis method bp neural network product variety fault diagnosis roller electrical system sample output experimental result fault diagnosis system fault detection
