Experimental study on characterization of mine wire rope detection signal properties based on magnetic field model

Electromagnetic detection is one of the reliable means of detecting mining wire rope defects. Based on the electromagnetic method of mining wire rope defect detection, there is a problem of unclear characterization law of defects and signal properties, and there are irrelevant signal properties in quantitative identification, which affects the accuracy of identification. The characterization relationship between the leakage signal characteristics and defect changes is summarized by using the method of three-dimensional magnetic dipole theory calculation, Maxwell simulation and experimental mutual verification. Firstly, the three-dimensional magnetic dipole theoretical model of steel wire rope under magnetic field environment is established, and the model is applied to the standard defects at the magnetic field theoretical calculations and Maxwell analog simulation; the peak/valley absolute value, wave width, peak/valley difference, peak/valley width of the theoretical and simulated values are extracted respectively, and the characterization analysis of the defects and the signals is carried out; finally, the design of defects is experimentally verified, and the experimental values of the Spearman correlation coefficients are obtained. The experimental results show that: the width and depth of defects are positively correlated with three signal eigenvalues of peak/valley absolute value, wave width and peak/valley difference, and there is no obvious correlation with peak/valley width; the length of defects shows a trend of increasing and then decreasing with peak/valley absolute value, and positively correlates with wave width, peak/valley difference and peak/valley width. And it is found that the width defect signal amplitude is the strongest, the length defect signal amplitude is the weakest, the depth signal amplitude is in the middle, and the peak/valley difference and peak/valley absolute value have the highest correlation with the defect. This study has certain engineering guidance value.