scholarly journals Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method

2017 ◽  
Vol 66 (4) ◽  
pp. 209-216
Author(s):  
Vitalij Nichoga ◽  
Liubomyr Vashchyshyn
Keyword(s):  
Magnetic Flux ◽  
Transverse Crack ◽  
Magnetic Flux Leakage ◽  
Rail Head ◽  
Railway Tracks ◽  
Further Development ◽  
Flux Leakage

In this article, the approach for detecting a transverse crack in the rail head via ANN with CWT and application created on its basis are presented. The ways of further development of the ANN for improving its work accuracy and the possibility of identification of other types of defects are also presented. Keywords: defect, transverse crack, CWT, ANN

scholarly journals Location Detection Method of Detector in Pipeline Using VMD Algorithm and Machine Learning Classifier

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1436
Author(s):  
Tuoru Li ◽  
Senxiang Lu ◽  
Enjie Xu
Keyword(s):  
Machine Learning ◽  
Magnetic Flux ◽  
Magnetic Flux Leakage ◽  
Intrinsic Mode Functions ◽  
Detection Range ◽  
Vibration Signals ◽  
Feature Vectors ◽  
Learning Classifier ◽  
Mode Decomposition ◽  
Flux Leakage

The internal detector in a pipeline needs to use the ground marker to record the elapsed time for accurate positioning. Most existing ground markers use the magnetic flux leakage testing principle to detect whether the internal detector passes. However, this paper uses the method of detecting vibration signals to track and locate the internal detector. The Variational Mode Decomposition (VMD) algorithm is used to extract features, which solves the defect of large noise and many disturbances of vibration signals. In this way, the detection range is expanded, and some non-magnetic flux leakage internal detectors can also be located. Firstly, the extracted vibration signals are denoised by the VMD algorithm, then kurtosis value and power value are extracted from the intrinsic mode functions (IMFs) to form feature vectors, and finally the feature vectors are input into random forest and Multilayer Perceptron (MLP) for classification. Experimental research shows that the method designed in this paper, which combines VMD with a machine learning classifier, can effectively use vibration signals to locate the internal detector and has the characteristics of high accuracy and good adaptability.

Alternative magnetic flux leakage modalities for pipeline inspection

1996 ◽  
Vol 32 (3) ◽  
pp. 1581-1584 ◽  
Author(s):  
G. Katragadda ◽  
W. Lord ◽  
Y.S. Sun ◽  
S. Udpa ◽  
L. Udpa
Keyword(s):  
Magnetic Flux ◽  
Magnetic Flux Leakage ◽  
Pipeline Inspection ◽  
Flux Leakage

GMR-based magnetic flux leakage technique for condition monitoring of steel track rope

2011 ◽  
Vol 53 (7) ◽  
pp. 377-381 ◽  
Author(s):  
W Sharatchandra Singh ◽  
B P C Rao ◽  
C K Mukhopadhyay ◽  
T Jayakumar
Keyword(s):  
Magnetic Flux ◽  
Condition Monitoring ◽  
Magnetic Flux Leakage ◽  
Flux Leakage
Sign in / Sign up

Export Citation Format

Share Document