Abstract
Roof accidents seriously affect the safe and efficient mining of the working faces. Therefore, it is necessary to assess and identify the possible and influencing factors on the occurrence of roof risk in a fully mechanized mining workface. In this study, based on the analytic hierarchy process and fuzzy comprehensive evaluation, a comprehensive standard cloud model was established through constructing a quantitative grade interval and calculating the weight of each index to achieve the aim of a roof risk assessment and identification. The accuracy of risk assessment was ensured by using the comprehensive analyses of various aspects, such as cloud digital features, risk assessment cloud image and standard cloud image. This showed that the main influencing factors on the occurrence of roof accidents were roof separation distance, weighting intensity and rib spalling followed by the coal body stress concentration, initial support force and geological conditions. Taking 42,115 fully mechanized working faces in the Yushen coal mining area as an engineering background, this model was adopted to assess and identify the risk of roof accidents through generating comprehensive assessment cloud images and introducing the Dice coefficient to calculate the similarity degree. The results showed that the overall risk of roof accidents in 42,115 working faces was regarded as grade II (general risk) through the overall index of comprehensive risk evaluation and a similarity degree of 0.8606. The impact of roof condition was mainly influenced by the risk of roof accidents, while the support status, personal working status and coal body condition had a limited effect on the risk of roof accidents. The comprehensive standard cloud model proposed in this study had strong visibility and discovered the key parts of risk indexes easily to solve the problems of ambiguity and quantitative identification in traditional roof risk evaluation methods. Therefore, this model was worth promoting, because it laid the foundation for the intelligent identification and early warning system of roof accident risk in a fully mechanized mining workface.
Highlights
The main disasters from underground coal mining activities in China involve coal dust, gas, water, fire, and roof accidents
A comprehensive risk evaluation cloud model of roof accidents was constructed based on the weight and standard grade level of each roof risk evaluation index
It effectively solved the problems of ambiguity and difficulty in quantitative expression and lacking visible results in the traditional risk evaluation methods of roof accidents
Summary
The main disasters from underground coal mining activities in China involve coal dust, gas, water, fire, and roof accidents. More serious is the fact that such roof accidents occurred in fully mechanized working faces, directly affecting the safety of mining activities, causing damage to machinery and equipment and even threatening the safety of several people [8,9,10,11,12,13]. It can be shown that the occurrence of roof accidents mainly depended on support condition, the mechanical properties of the roof, the quality of the personnel, and the stability of the coal body. The occurrences of roof accidents caused huge economic losses and more casualties, but they had serious effects on the coal mining community. It was necessary to strengthen the roof risk assessment and identify the fully mechanized mining workface to ensure the safety and productivity of coal mines
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