Technology of Magnetic Flux Leakage Signal Detection Based on Scale Transformation Stochastic Resonance

2006 ◽  
Author(s):  
Taiyong Wang ◽  
Shiguang Hu ◽  
Yonggang Leng ◽  
Ying Zhang ◽  
Li Zhao
Keyword(s):  
Magnetic Flux ◽  
Signal Detection ◽  
Stochastic Resonance ◽  
Magnetic Flux Leakage ◽  
Scale Transformation ◽  
Flux Leakage

Technology of Magnetic Flux Leakage Signal Detection Based on Scale Transformation Stochastic Resonance

2011 ◽  
Vol 141 ◽  
pp. 611-615
Author(s):  
Yong Sheng Peng ◽  
Yong Gang Leng ◽  
Jian Wan
Keyword(s):  
Magnetic Flux ◽  
Signal Detection ◽  
Stochastic Resonance ◽  
Magnetic Flux Leakage ◽  
Bistable System ◽  
Scale Transformation ◽  
Engineering Practice ◽  
Oil Well ◽  
Weak Signal Detection ◽  
Flux Leakage

The conception and realization of scale transformation stochastic resonance (STSR) are proposed, which are used to deal with problem of weak signal detection with large parameters that can not be resolved by traditional bistable system based on stochastic resonance. Magnetic flux leakage (MFL) signals inspection for oil well tubing defects is easily destroyed by noise. In order to detect weak MFL signals effectively, the proposed STSR technology is applied to the inspection. The result shows that the STSR technology has the potential application in engineering practice.

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
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