Improve the Quality of the Images Obtained by Magnetic Flux Leakage on Wire Ropes Using Wavelet Analysis

Defects in wire rope steel cables can be mainly due to corrosion, loss of cross-sectional metallic area and breakage of steel wires. These defects reduce the allowable strength of rope and eventually failure of the steel cable due to the stresses caused by the combined loads. This study aimed to identify and detect artificial defects on wire rope by using magnetic flux leakage method. First, a number of specific artificial faults created, which included the failure of cable steel wires. Then, using magnetic flux leakage device, the magnetic signals caused by artificial defects were received by magnetic sensors embedded in the device, and then displayed as a color image after analysis. Since the resolution of the images obtained from the magnetic sensor signals is not very clear, the wavelet analysis method has been applied on raw signals to improve quality of the image. In wavlet analysis signal decomposed into different frequency levels and the threshold criterion is applied to reduce the background noise. Then, from the frequency levels, the signal that best describes the faulty content is choosen and used to reconstruct the image. The results show that using the wavelet analysis method improves image analysis capability as well as image quality of the defect.