To realize the detection of multiple defects of pile foundation and improve the accuracy of defect type testing
a local feature analysis method is adopted to improve existing extraction methods of eigenvector and propose the mobile windows extraction method and matrix form of eigenvector based on pattern recognition and wavelet theory.Compared with existing methods
the window extraction method of eigenvector can identify two or more defect points in the same pile foundation
LVQ Neural Network Apply in Three Dimensional Object Recognition
A Method of Corona Discharge Pattern Recognition Based on T-S Fuzzy Neural Network
Improved YOLOv5s Algorithm for Defect Detection in Transmission Conductors with Small Targets
A Defect Detection Method for Flexible Thermal Control Film Manufacturing Process Driven by Digital Twin
The Effect of Temperature on the Impact Performance of the Down Blade in Rapid Rescue Scissor
Related Author
YU Xiao-yang
SUN Qiao
YUAN Hui-jiuan
L Shu-ming
ZHANG Zhong-lin
ZHENG Dian-chun
ZHAO Da-wei
MA Chun-jie
Related Institution
School of Measure-control Technology and Communication Engineering,Harbin University of Science and Technology,the Higher Educational Key Laboratory for Measuring &amp
School of Electrical and Electronic Engineering
(School of Mechanical Power Engineering, Harbin University of Science and Technology,,)