A Stable SINS/UWB Integrated Positioning Method of Shearer Based on the Multi-Model Intelligent Switching Algorithm

Abstract

The accurate stable measurement of position for a shearer is a key technology in realizing an automated fully mechanized coal mining face. Using as a base of SINS/UWB integrated positioning system, the signal interference and node damage of UWB often cause an invalid integrated positioning system, because of the bad working environment of the shearer in the coal mine. Consequently, the positioning accuracy of the SINS/UWB integrated system decreases quickly, due to the drift error of SINS. Aiming at two invalid styles include partial anchor node failure and all anchor nodes failure of UWB, this paper proposes a stable SINS/UWB integrated positioning system of a shearer using the multi-model intelligent switching method based on a tightly coupled integrated model and a decision tree fault-tolerant model. First of all, the tightly coupled integrated model and the decision tree fault-tolerant model are built using measured distance and the final position of UWB, respectively. Second, the multi-model intelligent switching algorithm can be established based on the shearer Markoff movement state and residual threshold judgment of a Kalman Filter. Finally, the experimental results show that the multi-model intelligent switching faulttolerant positioning algorithm can effectively overcome increased positioning error of the tightly coupled model and the decision tree model based on these two invalid styles. The maximum position error with the positioning model proposed in this paper is 0.93 m in 327 s, and the positioning accuracy with a multi-model intelligent switching model is much greater than that with tightly coupled integration and the decision tree fault tolerant models. INDEX TERMS Fault-tolerant integrated positioning system, multi-model intelligent switching algorithm, shearer, SINS/UWB, tightly-coupled, decision tree.

Online shearer-onboard personnel detection method for the intelligent fully mechanized mining face

“…Inspired by the weighted least squares (WLS) 23 and bilateral filter (BLF), 24 the GIF, a general linear translation-variant filter, was first defined, which involves a guidance image G selected according to the application, an input image X, and an output image Ẑ. 21 A linear model between the G and the ẐðpÞ in a predefined window # r ðp 0 Þ was assured as equation (1), and the whole algorithm is based on this assumption.…”

“…In recent years, many scholars focus on the research of intelligent fully mechanized mining technology and have achieved gratifying research results promoting the development of unmanned coal mining technology. [1][2][3] Fully mechanized mining face has the characteristics of low illumination and poor working environment. In intelligent fully mechanized mining face, shearer operation mode is changed from local control to remote control.…”

UWB indoor positioning optimization algorithm based on genetic annealing and clustering analysis

“…Analysis was based on the Gaussian noise environment, and further optimization was required in the complex environment. A stable SINS (Strapdown inertial navigation system)/UWB shearer integrated positioning system based on the multi-model intelligent switching method was previously proposed (Yang et al, 2019 ). The SINS/UWB shearer integrated positioning system was established based on the tightly coupled integration model and the decision tree fault-tolerant model.…”

A Novel Mobile Target Localization Approach for Complicate Underground Environment in Mixed LOS/NLOS Scenarios

“…To date, numerous researchers have conducted extensive studies on underground environment localization utilizing UWB positioning system. Yang et al [6] proposed a stable INS/UWB integrated positioning system of the shearer using the multi-model intelligent switching method based on a tightly coupled integrated model and a decision tree fault-tolerant model. Qin et al [7] studied a distributed UWB-based localization system in the underground mines, and the distributed localization algorithm based on particle swarm optimization was proposed for underground mines and implemented on the blind node.…”