• DocumentCode
    3747948
  • Title

    The study of nondestructive testing of rock bolts based on PNN and wavelet packet

  • Author

    Xiaoyun Sun;Fengning Kang;Hui Xing;Mingming Wang;Haiqing Zheng

  • Author_Institution
    Department of electrical and Electronic Engineering, Shijiazhuang Tiedao University, Shijiazhuang, China
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Anchoring technology is widely used in slope, tunnels and underground engineering. However, the quality of rock bolts is still a hot problem difficult to solve. Considering the shortcoming of pull-out testing, defect recognition in a nondestructive way is necessary. Decomposing the signals obtained by bolt quality detector with wavelet packet; extracting energy feature by wavelet packet energy spectrum; converting the normalized energy eigenvector as input of probabilistic neural network. With a higher accuracy than RBF, the PNN model can provide a reference for recognition defects of rock bolts in engineering without destruction.
  • Keywords
    "Wavelet packets","Fasteners","Rocks","Reflection","Neural networks","Feature extraction","Probabilistic logic"
  • Publisher
    ieee
  • Conference_Titel
    Modelling, Identification and Control (ICMIC), 2015 7th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICMIC.2015.7409489
  • Filename
    7409489