Ultra-wideband Positioning Method Based On Particle Swarm Optimization For Tunneling Support Bracket

As the main energy source of China,coal plays an important role in China economic development.In the small-scale tunneling operation of deep dangerous coal seams,the tunneling support bracket is a core component of the comprehensive tunneling equipment.On the one hand,it supports effectively the empty roof after tunneling,and on the other hand carries the anchor drilling rig to complete the anchor on the empty roof effectively.Therefore,its absolute position in the roadway determines directly the calibration of the bolt position in the subsequent anchoring operation and the safety of the tunneling roof.It can be seen that the positioning of the tunneling support bracket is crucial.Among existing positioning technologies of the tunneling support bracket,using inertial navigation technology is one of main positioning methods,but this method has error accumulation and requires correcting the inertial navigation element timely.This process is complicated and the orientation accuracy is not high.Considering that the working environment of the tunneling support bracket is closed and narrow coal mine roadway,and there is noise such as dust,positioning technologies such as GPS(which is applicable to the open ground environment)cannot be effectively detected.Based on this,the ultra-wideband technology(UWB)with high time resolution and strong anti-interference ability is introduced,and the three-dimensional positioning of the tunneling support bracket is accomplished.Firstly,in the traditional UWB TOA positioning model,the positioning equation is a nonlinear equation,which is difficult to be solved and has low accuracy.The Taylor series expansion method is able to used to find positioning solutions.However,the convergence and positioning accuracy of this method depend on exact initial positioning values.Based on this,this paper transforms the problem of solving nonlinear equations into an evolutionary optimization problem,constructs the fitness function of nonlinear equations,and uses particle swarm optimization(PSO)to determine a well initial value of optimal positioning equations.Furthermore,using Taylor series expansion,a optimal position information of the tunneling support bracket is obtained.The results show that the PSO-Taylor-based method has higher positioning accuracy.Secondly,in order to improve the accuracy of the UWB TDOA positioning model,the problem of solving the nonlinear equations is transformed into an evolutionary optimization problem.According to the solving process of Chan algorithm,the fitness function of nonlinear equations is constructed.After that,the exploratory particle swarm optimization(EPSO)is used to solve the TDOA positioning equations.The results show that the EPSO-based method has higher positioning accuracy.Finally,the error source of positioning system is systematically analyzed.To further improve the positioning accuracy,a method that changs the layout of the base station and the number of base stations is studied.The multi-objective UWB base station layout model is constructed,and an exploratory multi-objective particle swarm optimization(EMOPSO)algorithm is proposed to solve the base station layout model to obtain optimal layout scheme.Furthermore,the corresponding positioning equations are solved by the given PSO-Taylor algorithm and EPSO algorithm on the optimal layout and typical layout.The results show that the optimized layout scheme can help PSO-Taylor algorithm and EPSO algorithm get higher precision positioning results.