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Journal of Nondestructive Evaluation

, Volume 32, Issue 1, pp 37–43 | Cite as

Characterization of Wire Rope Defects with Gray Level Co-occurrence Matrix of Magnetic Flux Leakage Images

  • Donglai Zhang
  • Min Zhao
  • Zhihui Zhou
  • Shimin Pan
Article

Abstract

Magnetic flux leakage (MFL) techniques are used extensively for non-intrusively detecting and characterizing wire rope defects. Traditionally, MFL signals are captured with induction coil sensors. However, the output of coil sensors is related to the wire rope speed, and they can only provide the axial distribution along the wire rope. Hall sensors array are designed due to the limitation of coil sensors. In this paper, a Hall sensors array was designed to capture the MFL signals both axially and circumferentially. 30-channel data from Hall sensors are processed to compose a MFL image. A digital image process technique is introduced to preprocess the MFL image, the MFL images from different types of defects show different texture characteristics. Gray level co-occurrence matrix is utilized for feature extraction of the texture in the MFL image. Five typical eigenvalues (contrast, correlation, energy, homogeneity and entropy) are used as the inputs of back propagation (BP) networks. After training with typical samples, the BP networks show good performance in the quantitative recognition of different defects. The result of this work shows that texture analysis method for MFL image is suitable for feature extraction and quantitative detection of wire rope defects.

Keywords

Magnetic flux leakage image Wire rope defects Feature extraction Gray level co-occurrence matrix 

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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Donglai Zhang
    • 1
  • Min Zhao
    • 1
  • Zhihui Zhou
    • 1
  • Shimin Pan
    • 1
  1. 1.Harbin Institute of Technology Shenzhen Graduate SchoolShenzhenChina

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