Dynamic Precise Positioning Method of Shearer Based on Closing Path Optimal Estimation Model

摘要

Longwall shearer positioning with an inertial navigation system (INS) aided by an odometer is the key technology for automation of the longwall coal mining process. In order to improve the shearer positioning accuracy without using external sensors, the closing path motion characteristics of a shearer working in a longwall mining face was summarized by analyzing the longwall mining method. A closing path optimal estimation model was proposed based on the motion characteristics of the shearer and a Kalman filter (KF). Through simulation tests, it was verified that the model reduced the influence of heading angle drift of an INS on the shearer positioning accuracy without using external sensors. The shearer positioning accuracy based on the circular error probable was improved by approximately an order of one under the effect of the optimal estimation model. This was beneficial for reducing the large positioning error of the shearer in a longwall mining face during each cutting cycle for approximately 1 h.Note to Practitioners-This paper was motivated by the problem of longwall coal mining automation, especially positioning of longwall shearer, but it also applies to other mobile mining equipment. Longwall shearer positioning with an INS aided by an odometer has been regarded as an effective technological approach to longwall mining automation by coal mining workers and researchers. However, the positioning accuracy is largely subjected to the performance of the INS. This paper proposed a closing path optimal estimation model based on the motion characteristics of the shearer and a KF. Through simulation tests, it was verified that the model improved the positioning accuracy of the shearer by approximately an order of 1. This was beneficial for astricting the large positioning error of the shearer in a longwall mining face during each cutting cycle for approximately 1 h. In the future research, we will address the field tests of the closing path optimal estimation model and extending other mining applications.