The testing of wire rope is vital in ensuring personnel safety during coal mine production. At present, it has proven difficult to successfully pre-treat wire rope detection signals, leading to recognition errors and other issues. To this end, this paper details a proposed application of the morphological non-sampling wavelet method to the online detection signal processing of coal mine wire rope. Based on existing mathematical morphological theory, morphological filtering and morphological non-sampled wavelet construction methods, this paper constructs a morphological non-sampling wavelet method suitable for the online detection of the signal characteristics of mine wire rope. This method is then applied to signal preprocessing. The experimental results show that the developed method can effectively filter out noise such as baseline drift, that the signal-to-noise ratio (SNR) of the processed data is 39 dB > 30 dB and the elapsed time is 2 s. The SNRs obtained using the existing wavelet transform method and the morphological filtering method are 17 dB and 22-30 dB, respectively, with elapsed times of 1.99 s and 1.97 s, respectively. In this paper, the effective filtering of the signal is realised under the condition that the processing time of the signal preprocessing method shows no obvious increase.

The safety inspection of wire ropes is vital to ensure the safety of personnel and equipment. The detection of magnetic flux leakage is one of the most practical methods for evaluating the safety of wire ropes. However, compressing the data for this method has to date proven to be difficult. In this study, the lossless compression approach is adopted for data from defective sections of wire rope and the lossy compression approach is used for data from undamaged sections of wire rope. A lossless compression algorithm is then developed based on analysis of the structure and characteristics of the magnetic flux leakage signal. Here, a predictor, which was designed based on the correlation coefficient characteristics of the magnetic flux leakage signal, facilitates the removal of correlations between data from various sampling points. This reduces the information entropy, thereby enhancing the entropy coding efficiency and, in turn, helping to code the predictive error correctly. The experimental results show that for an information entropy of 4.0343 bits for the original signal, the lossless compression algorithm produces an average code length of 3.3 bits. This constitutes an average bit rate reduction of 0.7343 bits and a large reduction in the average number of bits for each data sample. It was found that the proposed algorithm ensures a high compression ratio. Furthermore, the signal-to-noise ratio of the recovery signal based on the proposed compression algorithm increased by 86%.

Existing methods for detecting magnetic leakage signals from damaged wire ropes require axial saturation magnetisation, and the accuracy of the detection equipment depends on the saturation degree of magnetisation. Moreover, the expected magnetisation effect is usually difficult to achieve owing to the special characteristics of the rope structure, diameter, and operating environment of the wire rope. Consequently, in addition to other issues, the detection accuracy and versatility of the equipment are low. In this study, a method based on spatial multidimensional orthogonal array loop magnetisation for detecting mine wire rope defects is proposed. Firstly, a new sensor excitation structure model is developed. Then a method of radiant magnetic flux of permanent magnet array is analysed, and the influence law of the number of permanent radiant magnetic blocks on the magnetisation effect is studied. In addition, a method of wire rope detection based on the principle of clustering is investigated, according to which the influence law of the shape, structure, and size of the polyurethane device on the effect of magnetisation is discussed. Finally, through laboratory experiments, the test model and proposed method are verified. The results show that the magnetisation effect is better and more cost-effective when the number of permanent magnet radiation magnetic block is n=8, and the proposed detection method can effectively distinguish damaged wire rope joints. Furthermore, the proposed equipment achieved signal-to-noise ratio of the signals, improving the reliability of damage detection.