Magnetic flux leakage testing (MFL) technology is widely used for the in-line inspection of ferromagnetic steel ropes. A common MFL tool is composed of permanent magnets that magnetize a rope axially to saturation and an array of magnetic sensors installed around the circumference of a probe to sense the leakage flux caused by discon-tinuities (such as broken wire, corrosion, and abrasions) in the rope. During actual testing of strand rope, the MFL discontinuity signals are submerged in the strand waveform signal—the magnetic signal of the surface of magnetized strand rope—and are difficult to detect. The MFL signal distortion is caused by the traditional filtering technique or wavelet signal processing technique. The error associated with quantitative detection of MFL is caused by this factor. The authors propose a technique of eliminating the influence of the strand waveform signal and enhancing the MFL signal based on the structure of strand rope. Complex nonlinear relationships exist between the size of discontinuities and the charac-teristic values of the MFL signal during quantitative detection; these relationships are combined with a neural network. The problem with the quantitative algorithm is the classification of broken wire numbers and the different discontinuity sizes are considered to be different classes. These tradi-tional techniques based on neural nets used in quantitative detection can determine the sizes of discontinuities in the parameter space for which the neural network is trained, so they require a variety of real samples to train the network in practical applications. In view of the aforementioned challenges, this paper proposes a new technique of quantitative analysis that trains the network without the need for a variety of real discontinuity samples, and obtains accurate results for actual discontinuities in strand rope.
Broomhead, D.S., and D. Lowe, 1988, “Multi-Variable Functional Interpo-lation and Adaptive Networks,” Complex Systems, Vol. 2, pp. 321–355.
Cao, Y., D. Zhang, C. Wang, and D. Xu, 2006, “More Accurate Localized Wire Rope Testing Based on Hall Sensor Array,” Materials Evaluation, Vol. 64, No. 9, pp. 907–910.
Dutta, S.M., F.H. Ghorbel, and R.K. Stanley, 2009, “Simulation and Analysis of 3-D Magnetic Flux Leakage,” IEEE Transactions on Magnetics, Vol. 45, No. 4, pp. 1966–1972.
Poggio, T., and F. Girosi, 1989, “A Theory of Networks for Approximation and Learning,” Massachusetts Institute of Technology Cambridge Artificial Intelligence Lab, Technical Report No. AI-M-1140.
Sharatchandra Singh, W., B.P.C Rao, and S. Vaidyanathan, 2007, “Detec-tion of Leakage Magnetic Flux from Near-Side and Far-Side Discontinuities in Carbon Steel Plates using a Giant Magneto-Resistive Sensor,” Measurement Science and Technology, Vol. 19, No. 1, pp. 1–8.
Stanley, R.K., 1995, “Simple Explanation of the Theory of the Total Magnetic Flux Method for the Measurement of Ferromagnetic Cross Sections,” Materials Evaluation, Vol. 53, No. 1, pp. 72–75.
Sun, Y., S. Liu, D. Li, Z. Ye, M. Gu, C. Liu, B. Feng, I. Temel, and Y. Kang, 2016, “Analyses of the Generating Mechanisms of Standard Magnetic Flux Leakage Testing Signals,” Materials Evaluation, Vol. 74, No. 6, pp. 909–918.
Trevino, D.A.G, S. Dutta, F. Ghorbel, and M. Karkoub, 2016, “An Improved Dipole Model of 3-D Magnetic Flux Leakage,” IEEE Transac-tions on Magnetics, Vol. 52, No. 12, pp. 1–7.
Wei, G., and C. Jianxin, 2002, “A Transducer Made Up of Fluxgate Sensors for Testing Wire Rope Discontinuities,” IEEE Transactions on Instrumenta-tion and Measurement, Vol. 51, No.1, pp. 120–124.
Weischedel, H.R., 1985, “The Inspection of Wire Ropes in Service: A Critical Review,” Materials Evaluation, Vol. 43, No. 13, pp. 430–437.
Weischedel, H.R., and R.P. Ramsey, 1989, “Electromagnetic Testing, a Reliable Method for the Inspection of Wire Ropes in Service,” NDT Inter-national, Vol. 22, No. 3, pp. 155–161.
Zhang, D., M. Zhao, and Z. Zhou, 2012, “Quantitative Inspection of Wire Rope Discontinuities Using Magnetic Flux Leakage Imaging,” Materials Evaluation, Vol. 70, No. 7, pp. 872–878.
Zhang, J., and X. Tan, 2016, “Quantitative Inspection of Remanence of Broken Wire Rope Based on Compressed Sensing,” Sensors, Vol. 16, No. 9, p. 1366.
48 Page Views
0 PDF Downloads
0 Facebook Shares