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Sensors 2016, 16(9), 1366; doi:10.3390/s16091366

Quantitative Inspection of Remanence of Broken Wire Rope Based on Compressed Sensing

1
College of Electrical Engineering, Henan University of Science and Technology, Luoyang 471023, China
2
Power Electronics Device and System Engineering Laboratory of Henan, Henan University of Science and Technology, Luoyang 471023, China
*
Author to whom correspondence should be addressed.
Academic Editors: Subhas Mukhopadhyay and Chinthaka Pasan Gooneratne
Received: 4 July 2016 / Revised: 14 August 2016 / Accepted: 22 August 2016 / Published: 25 August 2016
(This article belongs to the Special Issue Giant Magnetoresistive Sensors)
View Full-Text   |   Download PDF [3217 KB, uploaded 25 August 2016]   |  

Abstract

Most traditional strong magnetic inspection equipment has disadvantages such as big excitation devices, high weight, low detection precision, and inconvenient operation. This paper presents the design of a giant magneto-resistance (GMR) sensor array collection system. The remanence signal is collected to acquire two-dimensional magnetic flux leakage (MFL) data on the surface of wire ropes. Through the use of compressed sensing wavelet filtering (CSWF), the image expression of wire ropes MFL on the surface was obtained. Then this was taken as the input of the designed back propagation (BP) neural network to extract three kinds of MFL image geometry features and seven invariant moments of defect images. Good results were obtained. The experimental results show that nondestructive inspection through the use of remanence has higher accuracy and reliability compared with traditional inspection devices, along with smaller volume, lighter weight and higher precision. View Full-Text
Keywords: wire rope; remanence inspection; compressed sensing; wavelet filter; quantitative recognition wire rope; remanence inspection; compressed sensing; wavelet filter; quantitative recognition
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhang, J.; Tan, X. Quantitative Inspection of Remanence of Broken Wire Rope Based on Compressed Sensing. Sensors 2016, 16, 1366.

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