Research on the Shearer Positioning Method Based on SINS and LiDAR with Velocity and Absolute Position Constraints

Abstract

Accurate positioning of the shearer with a strapdown inertial navigation system (SINS) is the key technology to realize the automation of the longwall face. Unfortunately, the existing positioning methods have a strong dependence on the attitude accuracy of the SINS. The position errors gradually increase with the drift of the SINS attitude. To reduce the dependence on the SINS attitude and further increase the shearer positioning accuracy, this paper proposes a positioning method based on SINS and light detection and ranging (LiDAR) with velocity and absolute position constraints. A Kalman filter (KF) model based on these constraints was established. Simulation analysis shows that the attitude calibration between the shearer body, SINS and LiDAR, and the initial attitude alignment of the SINS are the keys to determining the shearer positioning accuracy. Even if there are small horizontal bends in the running track of the shearer and the features have small horizontal errors, an excellent positioning effect can still be obtained. In addition, four cutting processes were simulated with a reciprocating travel of 44.6 m and an advance distance of 1.2 m. Compared with the relative positioning method, the positioning accuracy of the proposed method was improved by 37%, 63%, 76%, and 69% from the first to the fourth cutting cycle, respectively, calculated by spherical error probable (SEP) values, and positioning accuracy had a lower dependence on the installation deflection angles between the SINS, the LiDAR, and the SINS attitude accuracy.

Research on the Shearer Positioning Method Based on the MEMS Inertial Sensors/Odometer Integrated Navigation System and RTS Smoother

“…In order to visually describe the accuracy improvement range of the proposed method, the spherical error probable (SEP) is calculated. The SEP is a universal evaluation method of 3D positioning accuracy [37], which is listed in Table 3. A1-A4 correspond to the first to fourth cutting cycles, respectively.…”

Application of an Automated Top Coal Caving Control System: The Case of Wangjialing Coal Mine

“…Estimating the duration of top coal caving requires one to accurately measure the actual thickness of the top coal in the pre-coal-caving phase [13,14]. Additionally, the real-time perception of the shearer's operating posture and position is crucial in determining whether the coal cave opening of the hydraulic support is opened [15,16]. The primary issue during top coal caving lies in accurately monitoring and analyzing the flow field of coal gangue while also predicting the optimal timing for closing the coal cave opening [17,18].…”

Simulation Optimization and Application of Shearer Strapdown Inertial Navigation System Modulation Scheme

“…The operating posture of a shearer, including the heading angle, pitch angle, roll angle, and 3D acceleration of the body and cutting part, is based on the three degrees of freedom dynamic information on the 3D space scale, which can determine the position of the shearer and predict the 3D extension direction of the working face in the coal-bearing geological space. The operating posture is also the basic information for realizing the shearer's memory cutting, automatic height adjustment, intelligent control, intelligent perception, remote visual monitoring [1,2], etc. As a difficult problem of intelligent mining equipment, accurate perception of the shearer's running attitude can not only provide a way to detect and predict the production status of the intelligent chemical working face but also provide data feedback for the autonomous intelligent control of the shearer.…”