Abstract
The accurate measurement of position and orientation for shearers is a key technology in realizing an automated, fully-mechanized, coal mining face. Since Global Positioning System (GPS) signal cannot arrive at the coal mine underground, wireless sensor network positioning system cannot operate stably in the coal mine; thus a strap-down inertial navigation system (SINS) is used to measure the position and orientation of the shearer. Aiming at the problem of the SINS accumulative error, this paper proposes a positioning error correction method based on the motion constraint-aided SINS zero velocity updated (ZUPT) model. First of all, a stationary state detection model of the shearer is built with median filter based on the acceleration and angular rate measured by the SINS. Secondly, the motion of the shearer is analyzed using coal mining technology, then the motion constraint model of the shearer is established. In addition, the alternate action between the motion constraint model and the ZUPT model is analyzed at the process of movement and cessation of the shearer, respectively; hence, the motion constraint-aided SINS ZUPT model is built. Finally, by means of the experimental platform of the SINS for the shearer, the experimental results show that the maximum position error with the positioning model proposed in this paper is 1.6 m in 180 s, and increases by 92.0% and 88.1% compared with the single motion constraint model and single ZUPT model, respectively. It can then restrain the accumulative error of the SINS effectively.
Highlights
Coal is the principal basic energy and raw material in China
With full consideration of the motion constraint characteristic of the shearer in a fully-mechanized working face, the zero velocity updated (ZUPT) model can be built with a Kalman filter (KF) based on the transient stationary process of the shearer, according to the stationary state detection algorithm
After the shearer finishes cutting an entire row of coal and moves from one side of the fully mechanized coal mining face to the other side, which likes from point A to point B in Figure 2, the hydraulic supports behind the shearer have already pushed scraper conveyer with a distance in the advance direction of working face
Summary
Coal is the principal basic energy and raw material in China. To meet the requirements for the development of the national economy, coal has been considered to be the main energy source for a long time to come [1]. The “three-machine” of a fully-mechanized coal face includes the shearer, scraper conveyer, and hydraulic support. Due to the drift of low-cost MEMS sensors and recursive computation, Rui et al [17] proposed a zero velocity update (ZUPT) method for pedestrian tracking based on foot-mounted inertial sensors suffering from accumulative velocity and position errors. Aiming at the above problems, this paper analyzes the motion characteristics of the shearer and proposes a measured error correction strategy for the SINS using ZUPT and motion constraint methods. With full consideration of the motion constraint characteristic of the shearer in a fully-mechanized working face, the ZUPT model can be built with a Kalman filter (KF) based on the transient stationary process of the shearer, according to the stationary state detection algorithm. The corrected position solution model of the SINS is built based on the motion constraint of the shearer. The motion constraint-aided SINS ZUPT positioning model of the shearer can be obtained
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