Fault detection of train mechanical parts using multi-mode aggregation feature enhanced convolution neural network

Author(s):  
Ye Tao ◽  
Zhang Jun ◽  
Zhang Zhi-hao ◽  
Zhang Yi ◽  
Zhou Fu-qiang ◽  
...  
Author(s):  
Yan Wang ◽  
Weijie Zhang

Aiming at the problem of low detection accuracy of traditional power insulator fault detection methods, a power insulator fault detection method based on deep convolution neural network is designed. For the training of deep convolution neural network, the fault detection of power insulator based on deep convolution neural network is realized by anchor design, loss function design, candidate region selection mechanism establishment and sharing convolution features. The experimental results show that the fault detection method of power insulator based on deep convolution neural network is more accurate than the traditional method, and the detection time is less.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 140632-140642 ◽  
Author(s):  
Sang-Hun Kim ◽  
Dong-Yeon Yoo ◽  
Sang-Won An ◽  
Ye-Seul Park ◽  
Jung-Won Lee ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document