Pile Defect Intelligent Identification based on Wavelet Analysis and Neural Networks

摘要

In view of the phenomenon of pile test results are greatly influenced by human, the paper puts forward that to combine wavelet analysis and neural network for pile testing, use the extreme value point of the wavelet analysis as the input of neural networks, depending on the output codes to determine the defect types and position. And it is believed that there is a good potential for use in future.