Relative Position and Posture Detection of Hydraulic Support Based on Particle Swarm Optimization

Abstract

The position and posture of the hydraulic support seriously affect the efficiency of coal mining and the safety of coal production. However, most of the current detection technologies have poor reliability, and the detection methods are difficult to adapt to the complex environment of coal mines. To effectively monitor the hydraulic support, and thereby improve the efficiency of coal mining, we propose a new method to detect the relative position and posture of the hydraulic support. The method is based on the mathematical idea that three points can determine a plane. Firstly, we use angle sensors and displacement sensors to build the detection device, use STM32 microprocessor to collect data, and realize real-time display of the data on the PC. Then, we conduct a single point detection experiment and a plane moving experiment, and combined the particle swarm optimization (PSO) algorithm to optimize the data. Experiment results show that the relative error of the single-point detection can reach 0.53%. Thirdly, we carry out a detection experiment of three points on the plane. Experiment results show that the detection accuracy of the two planes can reach 0.2°. Finally, to test the monitoring effect of the detection device on the hydraulic support, we carry out the relative position and posture detection experiment of the canopy. The experiment results show that the device can effectively detect the posture change of the canopy when the hydraulic support are moving. The method we use is contact measurement, which has high reliability and strong stability. The research on the relative position and posture detection of hydraulic support provides a reliable method to monitor the support working status. It lays the foundation for the intelligent control of the mining working face straightness and the perception of the support posture.

Research on control strategy of asymmetric electro-hydraulic servo system based on improved PSO algorithm

“…It is used to optimize nonlinear systems in literature. [13][14][15][16][17][18] However, the traditional particle swarm optimization algorithm is easy to fall into the local optimal solution. At present, the improved particle swarm optimization algorithm introduces other control methods or intelligent algorithms to deal with complex objects.…”

Pushing Pose Sensing of Underground Mobile Supporting Robot

“…At present, the sensing approach for pose and straightness of hydraulic support mainly focus on simple on-site pull wire and infrared beam measurement. With the deep integration of intelligent detection technology into coal mine production, the inertial navigation technology [6,7], Unity3D technology [8][9][10][11], and visual technology [12,13] have been used gradually. Zhang et al and Chen et al [3,14] proposed a pose monitoring method of hydraulic support based on multisensor fusion technology.…”

“…e pushing pose of MSR refers to the pose state formed by the middle groove of the scraper conveyor when MSR pushes forward with the working face, pushed and moved periodically [2]. In the process of coal mining, MSR, scraper conveyor, and coal wall need to maintain a certain straightness to ensure the smooth operation of coal mining equipment [3][4][5][6]. However, the pushing pose of MSR is the essential factor for the straightness of the working face.…”

A Deep Learning Approach for Evaluating the Efficacy and Accuracy of PoseNet for Posture Detection

“…Constructed upon the foundation of TensorFlow.js, ml5.js is an intuitive and accessible library that streamlines the execution of intricate machine learning algorithms, such as PoseNet. This framework has facilitated widespread access to machine learning, enabling individuals with rudimentary knowledge of JavaScript to incorporate advanced models into their web applications (Gao et al, 2020). The provision of accessibility through ml5.js is an essential component in facilitating the extensive implementation and exploration of AI technologies in various domains, such as education, the arts, and interactive digital experiences.…”