Abstract

In the field of nondestructive testing (NDT) of wire rope, magnetic flux leakage (MFL) detection is the most widely used method. The traditional single-dimensional MFL detection system has the disadvantages of large volume, heavy weight, low sensitivity and low recognition rate. In order to overcome these problems, this paper designed the three-dimensional MFL acquisition system based on unsaturated magnetic excitation using the tunnel magnetoresistive (TMR) elements and proposed the three-dimensional MFL detection method. We mapped the three-dimensional MFL signals after noise reduction to Red-Green-Blue (RGB) space for color imaging. Then, the localization and segmentation algorithms were used to crop color images of broken wire defects. Finally, the color moment eigenvalues of color images of six types broken wire defects were extracted as the input of the back propagation (BP) neural network to quantitatively identify the broken wires. From the experimental results of the quantitative identification of broken wire defects, it can be seen that it is feasible to use the color images of the three-dimensional MFL signals to quantitatively identify the broken wire defects. Moreover, the three-dimensional MFL color imaging can effectively improve the recognition rate of broken wires.

Highlights

  • Wire rope has the advantages of good elasticity, light weight and strong tensile resistance

  • We proposed the color imaging technology based three-dimensional magnetic flux leakage (MFL) signals, which mapped the radial component, tangential component, and axial component of MFL signals to the RGB color spaces

  • EXPERIMENTAL RESULTS AND ANALYSIS Quantitative identification of broken wire defects is a crucial goal in the research of nondestructive testing (NDT) of wire rope

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Summary

Introduction

Wire rope has the advantages of good elasticity, light weight and strong tensile resistance. J. Zhang et al.: Quantitative Detection of Wire Rope Based on Three-Dimensional MFL Color Imaging Technology no leakage of the magnetic field signals on the surface of the component.

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Conclusion
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