Travel Dynamics Analysis and Intelligent Path Rectification Planning of a Roadheader on a Roadway

Xiaodong Ji, Minjun Zhang, Yuanyuan Qu, Hai Jiang and Miao Wu
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Xiaodong Ji: School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Minjun Zhang: Steta Key Laboratory of Tribology, Department of Precision Instruction, Tsinghua University, Beijing 100084, China
Yuanyuan Qu: School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Hai Jiang: School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Miao Wu: School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China

Energies, 2021, vol. 14, issue 21, 1-21

Abstract: The tunneling work belongs to the group operation of semi-closed space, and the work is difficult with a high risk coefficient. It is an urgent requirement of coal mining to achieve unmanned and intelligent tunneling work. The path rectification planning of roadheaders is a necessary step before roadway cutting. In the traditional dynamic modeling analysis of roadhead tracks, problems such as compaction resistance, bulldozing resistance, steering resistance, tunnel dip angle, ditching, and obstacle-crossing capacity are not considered. In order to approximate the kinematic and dynamic parameters of a roadheader’s deviation correction under actual working conditions, this paper establishes kinematic and dynamic models of a roadheader’s path rectification at low speeds and under complex working conditions, and calculates the obstacle-crossing ability of roadheaders in the course of path rectification by modes based on roadway conditions, crawler resistance, and driving performance of the roadheader. Field experiments were carried out to verify the effectiveness of the dynamic model. The dynamic roadheader model was used in combination with actual working conditions of roadways in order to establish a roadway grid model. The grid model was simplified using rectifying influence degree and distance cost. The roadheader dynamic model and grid model were then used to propose a path rectification planning and tracking algorithm based on particle swarm optimization of the actual roadway conditions and roadheader driving performance. Finally, the effectiveness and superiority of the algorithm were verified using MATLAB simulation. The algorithm can provide strong technical guarantee for the intelligence of roadheader and unmanned mining. The results presented here can provide theoretical and technical support for the structural optimization and intelligent travel control of roadheaders.

Keywords: roadheader; dynamics analysis; rectification plan; particle swarm optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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