Research on multi-boom coordinated drilling technology for hard rock tunneling

In order to realize the mechanized construction of hard rock tunnel boring, and improve the construction efficiency of three-boom drilling jumbo when applied to hard rock tunnel boring, the research and analysis are conducted on the positioning accuracy of three-boom drilling jumbo borehole and the optimization of multi-boom cooperative borehole path. Firstly, the kinematic model of three-boom drilling jumbo is established based on the D-H method, and the effective working space of three-boom drilling jumbo is obtained by Monte Carlo method, and the RBF neural network algorithm is used to realize the accurate positioning of drill boom borehole. Secondly, an improved genetic algorithm is implemented to optimize the hole sequence of the three-boom drilling jumbo with the shortest moving distance of the end of the drill boom and the minimum sum of the joint variables during the movement of the drill boom as the optimization objectives, and it is compared with two existing hole sequence planning algorithms, namely, the ant colony optimization algorithm and the adaptive genetic algorithm. Finally, a numerical simulation is conducted to analyze the collision interference of multiple drill booms with two different drilling sequences and the divided working space. The numerical simulation results show that: ① The maximum drilling positioning error of the three drill booms is 2.94 mm, and the error is controlled within 3%. ② Compared with two existing hole sequence planning algorithms, the total distance traveled at the end of three drill boom are shortened by 5.39 m and 10.84 m, respectively, when the shortest distance traveled at the end of drill boom is taken as the optimization objective; the sum of each joint variable of three drill boom are reduced by 2.76 rad and 5.34 rad, respectively, when the minimum sum of joint variables is taken as the optimization objective. ③ The shortest distance between the middle drill boom and the left and right drill boom is 984.6 mm and 580.8 mm respectively, when the drilling operation is carried out in the drilling sequence with the shortest distance, there will be no collision and interference between the drill booms, but when the drilling operation is carried out with the smallest hole sequence scheme of joint variables, the shortest distance between the middle drill boom and the left drill boom is 193.5 mm, considering the structure size of the drill boom and safety, and collision may occur. In summary, the RBF neural network algorithm can achieve precise positioning of the borehole and improve the efficiency of hard rock tunneling when the borehole sequence is constructed based on the shortest distance as the optimization objective, which provides theoretical support for hard rock tunneling construction.