The optimization of an integrated coal gangue system of mining, dressing, and backfilling in deep underground mining is a multi-objective and complex decision-making process, and the factors such as spatial layout, node location, and transportation equipment need to be considered comprehensively. In order to realize the intellectualized location of the nodes for the logistics and transportation system of underground mining and dressing coal and gangue, this paper establishes the model of the logistics and transportation system of underground mining and dressing coal gangue, and analyzes the key factors of the intellectualized location for the logistics and transportation system of coal and gangue, and the objective function of the node transportation model is deduced. The PSO–QNMs algorithm is proposed for the solution of the objective function, which improves the accuracy and stability of the location selection and effectively avoids the shortcomings of the PSO algorithm with its poor local detailed search ability and the quasi-Newton algorithm with its sensitivity to the initial value. Comparison of the particle swarm and PSO–QNMs algorithm outputs for the specific conditions of the New Julong coal mine, as an example, shows that the PSO–QNMs algorithm reduces the complexity of the calculation, increases the calculation efficiency by eight times, saves 42.8% of the cost value, and improves the efficiency of the node selection of mining–dressing–backfilling systems in a complex underground mining environment. The results confirm that the method has high convergence speed and solution accuracy, and provides a fundamental basis for optimizing the underground coal mine logistics system. Based on the research results, a node siting system for an integrated underground mining, dressing, and backfilling system in coal mines (referred to as MSBPS) was developed.
The dynamic hazards in the open face area caused by the impact load of the massive strong roof become increasingly severe with the increase in the cutting height of the longwall face and its depth of cover. Understanding the strata-shield interaction under the dynamic impact loading condition may relieve the dynamic hazards. In this paper, a 3D physical modelling platform is developed to study the interaction between the roof strata and the longwall shield under the dynamic impact load conditions. A steel plate is dropped to the coal face wall at a certain height above the immediate roof to simulate the free fall of the main roof and the dynamic impact loading environment. The occurrence of major roof falls is modelled at different height above the model and at different positions relative to the longwall faceline. The large-cutting-height and top-coal-caving mining methods are modelled in the study to include the nature of the immediate roof. The results show that the level of face and roof failures depends on the magnitude of the dynamic impact load. The position and height of the roof fall have an important influence to the stability of the roof and face. The pressures on the shield and the solid coal face are relieved for the top-coal-caving face as compared to the large-cutting-height face.
The second-order sliding mode control has strong robustness. Its application has greatly improved the anti-jamming ability of permanent magnet synchronous motor(PMSM) speed control systems. However, the influence of noise is unavoidable due to the introduction of a differentiator in the second-order sliding mode control, and the steady-state performance of the system is poor due to the absence of a q-axis current loop. This paper proposes a second-order sliding mode control method based on singular perturbation, which decouples the PMSM speed control system into two subsystems, the slow subsystem, including the speed variable, adopts second-order sliding mode control, and the fast subsystem, including the current variable of q-axis, adopts linear control. The design of a sliding surface for the slow subsystem avoids the application of the differentiator, which reduces the chattering better. Besides this, the steady-state performance of the system is improved due to the introduction of the feedback current of the q-axis. Experimental results show that the proposed method has strong robustness and can achieve high-precision control.
Physical simulation is one of the effective methods to study mining problems, but the selection and proportion of simulation materials are greatly affected by the regional environment. This paper is based on a multilevel orthogonal design test scheme using sand, lime, and gypsum as the materials in the Shangwan coal mine in the Shendong coalfield, with the sand to cement ratio, paste to ash ratio, and maintenance days as variables. The effect of the polar difference method on the strength and density of gypsum was used as a reference for physical simulation in the Shendong coalfield. The sensitivity analysis of each factor was carried out by the polar difference method, and the influencing factors on density were, in descending order, sand to mortar ratio, mortar to ash ratio, and the number of maintenance days; the influencing factors on strength were, in descending order, mortar to ash ratio, maintenance days, and sand to mortar ratio. The sand cement ratio was negatively correlated with strength and density, the paste to ash ratio was positively correlated with strength and density, and the number of maintenance days was positively correlated with strength and negatively correlated with density. The multivariate non-linear regression analysis of sand to cement ratio and paste to ash ratio identified similar material proportioning test equations for the Shendong coalfield, which can improve the accuracy of physical simulation and be used to guide physical simulation experiments in the Shendong coalfield.
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