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基于MEMS惯性传感器/里程计组合导航系统和RTS平滑器的采煤机定位方法研究

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

作者信息

Zheng Jiangtao, Li Sihai, Liu Shiming, Guan Bofan, Wei Dong, Fu Qiangwen

机构信息

School of Automation, Northwestern Polytechnical University, Xi'an 710072, China.

出版信息

Micromachines (Basel). 2021 Dec 8;12(12):1527. doi: 10.3390/mi12121527.

Abstract

The shearer positioning method with an inertial measurement unit and the odometer is feasible in the longwall coal-mining process. However, the positioning accuracy will continue to decrease, especially for the micro-electromechanical inertial measurement unit (MIMU). In order to further improve the positioning accuracy of the shearer without adding other external sensors, the positioning method of the Rauch-Tung-Striebel (RTS) smoother-aided MIMU and odometer is proposed. A Kalman filter (KF) with the velocity and position measurements, which are provided by the odometer and closing path optimal estimation model (CPOEM), respectively, is established. The observability analysis is discussed to study the possible conditions under which the error states of KF can be estimated. A RTS smoother with the above-mentioned KF as the forward filter is built. Finally, the experiments of simulating the movement of the shearer through a mobile carrier were carried out, with a longitudinal movement distance of 44.6 m and a lateral advance distance of 1.2 m. The results show that the proposed method can effectively improve the positioning accuracy. In addition, the odometer scale factor and mounting angles can be estimated in real time.

摘要

基于惯性测量单元和里程计的采煤机定位方法在长壁采煤过程中是可行的。然而,定位精度会持续下降,尤其是对于微机电惯性测量单元(MIMU)。为了在不增加其他外部传感器的情况下进一步提高采煤机的定位精度,提出了基于Rauch-Tung-Striebel(RTS)平滑器辅助的MIMU和里程计的定位方法。分别利用里程计和闭合路径最优估计模型(CPOEM)提供的速度和位置测量值建立了卡尔曼滤波器(KF)。讨论了可观性分析,以研究能够估计KF误差状态的可能条件。构建了以上述KF作为前向滤波器的RTS平滑器。最后,通过移动载体进行了模拟采煤机运动的实验,纵向移动距离为44.6 m,横向推进距离为1.2 m。结果表明,所提方法能有效提高定位精度。此外,还能实时估计里程计比例因子和安装角度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c38/8707076/de07069711f2/micromachines-12-01527-g003.jpg

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