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Fault Detecting Technology Based on BP Neural Network Algorithm

  • Ran Jin
  • Kun Gao
  • Zhigang Chen
  • Chen Dong
  • Yanghong Zhang
  • Lifeng Xi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4693)

Abstract

This paper describes an automatic online detecting system. In the system, digital image processing technology is used to preprocess X-ray images of the products, and neural network algorithm is applied to diagnose faults. The fault recognition model adopts an improved back-propagating neural network, which is trained by a series of standard X-ray images of correctly assembled products. The detecting system combines digital radiography technology with digital image processing, and applies the back-propagating neural network algorithm in the fault recognition process. The system improves the speed and reliability of fault detection and has application in the field of industrial nondestructive detection.

Keywords

nondestructive detection fault diagnosis neural networks image processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ran Jin
    • 1
  • Kun Gao
    • 1
  • Zhigang Chen
    • 1
  • Chen Dong
    • 1
  • Yanghong Zhang
    • 1
  • Lifeng Xi
    • 1
  1. 1.School of Computer Science And Information Technology, Zhejiang Wanli University, Ningbo, Zhejiang 315100P.R. China

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