Application of artificial neural networks in sonic diagnosis of cracking hammer with artificial diamond

  • Li Kai-yang
  • Hu Yao-gai
  • Zhong Yu-ning


On the basis of the characteristic parameters selected from the fault sonic signals of cracking hammer with artificial diamond by means of with time series analysis and time domain statistics, three-layer artificial neural network is trained by an improved BP algorithm. The results state that the fault sonic signals can be identified by trained network system precisely.

Key words

time series analysis artificial neural networks sonic diagnosis 

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Copyright information

© Springer 1999

Authors and Affiliations

  • Li Kai-yang
    • 1
  • Hu Yao-gai
    • 1
  • Zhong Yu-ning
    • 2
  1. 1.Department of Analysis-Measurement ScienceWuhan UniversityWuhanChina
  2. 2.Department of Mechanical EngineeringHubei Polytechnic UniversityWuhanChina

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