Abstract:In order to realize the autonomous cutting for tunneling robot, the method of cutting trajectory planning of sections with complex composition was proposed. Firstly, based on the multi-sensor parameters, the existence, the location, and size of the dirt band were determined. The roadway section environment was modeled by grid method. Secondly, according to the cutting process and tunneling cutting characteristics, the cutting trajectory ant colony algorithm was proposed. To ensure the operation safety and avoi… Show more
“…Using this torque sensor, the total cutting resistance torque is measured, as the cutting head cuts rock, at a specific horizontal swing speed (1.106 m·min −1 ) and at a set rotational speed (46.701 r·min −1 ). 31,32 The underground working process of the cutting head, in a certain mining area in Shandong province, is shown in Figure 18. Figure 17.Components of cutting unit.Figure 18.Working process of cutting head underground.…”
Section: Optimization Of Spiral Angle Of Cutting Headmentioning
The cutting head is the key component of a road header in tunnel excavation, where the concept of the spiral angle design directly affects the comprehensive performance, which includes cutting resistance, fluctuation coefficient, specific energy consumption, cutting head stress distribution, and so on. Based on the theory of rock-breaking by pick, the mechanical model of pick was established, and the three-dimensional force vector in the WORKBENCH coordinate system was determined. The 3D model of the proposed cutting head was designed using PRO/E and the static simulation was carried out using WORKBENCH, while the stress information of key parts was obtained. Furthermore, a four-dimensional fitting method was used to investigate the influence of the horizontal swing speed, rotational speed, and spiral angle of the cutting head, on the stress of the cutting head assembly. By setting the horizontal swing speed, rotational speed and the spiral angle as design variables and the specific energy consumption, total cutting resistance, fluctuation coefficient, power consumption, and stress on cutting head assembly as the objective function; the multiobjective optimization function of the cutting head was established. By using genetic algorithm, the complex problem has been solved. The solution of this optimization function provides the horizontal swing speed, rotational speed, and spiral angle values, where the optimal performance is achieved, in the aspect of energy consumption, cutting resistance, fluctuation coefficient, cutting power, and cutting motor power. This method provides solid guidance and is a great reference in spiral angle design and optimization.
“…Using this torque sensor, the total cutting resistance torque is measured, as the cutting head cuts rock, at a specific horizontal swing speed (1.106 m·min −1 ) and at a set rotational speed (46.701 r·min −1 ). 31,32 The underground working process of the cutting head, in a certain mining area in Shandong province, is shown in Figure 18. Figure 17.Components of cutting unit.Figure 18.Working process of cutting head underground.…”
Section: Optimization Of Spiral Angle Of Cutting Headmentioning
The cutting head is the key component of a road header in tunnel excavation, where the concept of the spiral angle design directly affects the comprehensive performance, which includes cutting resistance, fluctuation coefficient, specific energy consumption, cutting head stress distribution, and so on. Based on the theory of rock-breaking by pick, the mechanical model of pick was established, and the three-dimensional force vector in the WORKBENCH coordinate system was determined. The 3D model of the proposed cutting head was designed using PRO/E and the static simulation was carried out using WORKBENCH, while the stress information of key parts was obtained. Furthermore, a four-dimensional fitting method was used to investigate the influence of the horizontal swing speed, rotational speed, and spiral angle of the cutting head, on the stress of the cutting head assembly. By setting the horizontal swing speed, rotational speed and the spiral angle as design variables and the specific energy consumption, total cutting resistance, fluctuation coefficient, power consumption, and stress on cutting head assembly as the objective function; the multiobjective optimization function of the cutting head was established. By using genetic algorithm, the complex problem has been solved. The solution of this optimization function provides the horizontal swing speed, rotational speed, and spiral angle values, where the optimal performance is achieved, in the aspect of energy consumption, cutting resistance, fluctuation coefficient, cutting power, and cutting motor power. This method provides solid guidance and is a great reference in spiral angle design and optimization.
“…Furthermore, the vision systems allow analyzing the rock structure on the heading face of the roadway, and can therefore be applied, for example, in the selective mining of rocks of different hardness in automatic mode [12][13][14]. Among the tasks that should be solved for automation of the cutting process is the planning of the optimal trajectory of the cutting heads [15][16][17].…”
The process of cutting rocks with a boom-type roadheader results in extreme dynamic loads and vibrations. Mining, especially in the case of hard rocks, is associated with large energy consumption, which, when combined with low process efficiency, can lead to low drilling performance. These phenomena are undesirable because excessive dynamic load leads to low machine durability, as well as deterioration of work conditions and safety. Low mining efficiency affects the economics of mining works conducted using roadheaders. However, these adverse effects can be minimized by optimizing the cutting process, thanks to the automatic control of the roadheader. The present article discusses the concept of automatic control of a boom-type roadheader’s cutting heads movement. Based on previously conducted computer investigations, it was assumed that reducing the energy consumption of the cutting process and improving the dynamic state of the roadheader (objective functions) are possible only by controlling three of the four parameters characterizing the cutting process: angular speed of the cutting heads, boom swinging speed, and cut height. The web of cut and workability of the rock can be treated as variables of a stochastic nature. This paper presents selected results of computer tests during simulated cutting of rocks with different uniaxial compressive strengths (UCS) in automatic and manual mode. In addition, the tests studied the behavior of the roadheader during the cutting of rocks with variable workability, which is typical of drilling excavations in a layered rock mass. The results of simulated cutting in automatic and manual mode were compared to assess the effectiveness of the adopted automatic control strategy. It was found that the algorithm developed for automatic control of the cutting heads’ movement allows reducing the consumption of cutting energy by up to half compared to the consumption during cutting in manual mode. Furthermore, it was found to improve the dynamic state of the machine.
“…e cutting arm, which is the key cutting component of the roadheader, is driven by a hydraulic cylinder. e working process of a roadheader is to cut coal and rock using the swing of the cutter arm and the rotation of the cutter head [7][8][9]. During tunneling, the constantly changing cutting load can cause the cutting motor load power to be extremely unstable, leaving the roadheader in an under-or overloaded state, which undermines the cutting efficiency [10][11][12][13].…”
A multiparameter control strategy and method for the cutting arm of a roadheader is proposed through the operation analysis of roadheader. The method can address the problems of low intelligence and low cutting efficiency faced by the roadheader in the cutting process. The control strategy is divided into two parts: the cutting load identification part and the swing speed control part. The former part is designed using a backpropagation neural network that is optimized by an improved particle swarm optimization algorithm. The latter part is optimally designed using a fuzzy PID controller with improved simulated annealing particle swarm optimization. The simulation analysis in SIMULINK showed that the response time was reduced, proving the robustness of the method. In addition, experimental studies verified the good control effect of the method under different cutting states. The proposed method uses multiparameter to intelligently change the swing speed, providing a theoretical and practical basis for the realization of intelligent and unmanned cutting of roadheader.
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