Abstract
In the coal mining process, the destabilization of loaded coal mass is a prerequisite for coal and rock dynamic disaster, and surface cracks of the coal and rock mass are important indicators, reflecting the current state of the coal body. The detection of surface cracks in the coal body plays an important role in coal mine safety monitoring. In this paper, a method for detecting the surface cracks of loaded coal by a vibration failure process is proposed based on the characteristics of the surface cracks of coal and support vector machine (SVM). A large number of cracked images are obtained by establishing a vibration-induced failure test system and industrial camera. Histogram equalization and a hysteresis threshold algorithm were used to reduce the noise and emphasize the crack; then, 600 images and regions, including cracks and non-cracks, were manually labelled. In the crack feature extraction stage, eight features of the cracks are extracted to distinguish cracks from other objects. Finally, a crack identification model with an accuracy over 95% was trained by inputting the labelled sample images into the SVM classifier. The experimental results show that the proposed algorithm has a higher accuracy than the conventional algorithm and can effectively identify cracks on the surface of the coal and rock mass automatically.
Highlights
Coal and rock dynamic disasters have become a great threat to the safe and efficient production of coal mines due to their sudden, rapid development, wide range and large degree of damage
Systematic research on coal and rock dynamic disasters has revealed that targeted monitoring means and preventive measures have already become a major problem in the field of coal mine safety
A method for detecting the surface cracks for loaded coal using a vibration failure process based on a vibration failure test system and support vector machine (SVM) was proposed and developed
Summary
Coal and rock dynamic disasters have become a great threat to the safe and efficient production of coal mines due to their sudden, rapid development, wide range and large degree of damage. Systematic research on coal and rock dynamic disasters has revealed that targeted monitoring means and preventive measures have already become a major problem in the field of coal mine safety. Different stress states and stress levels will lead to different forms of coal and rock damage. The most direct manifestation of these failure modes is the production of cracks on the surface of the coal and rock mass. The accurate detection and analysis of these cracks can provide important guidance for preventing and controlling the destabilization of coal and rock and improving the safety of underground personnel. Accurate and timely detection of cracks in the front coal wall can effectively prevent
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