Qu Song, Bao Zhongxu, Yin Yuqing, Yang Xu
School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221000, China.
Technical Department, Xuzhou Kerui Mining Technology Co., Ltd., Xuzhou 221000, China.
Sensors (Basel). 2022 Aug 29;22(17):6511. doi: 10.3390/s22176511.
Accurate localization in underground coal mining is a challenging technology in coal mine safety production. This paper proposes a low-cost battery-free localization scheme based on depth images, called MineBL. The main idea is to utilize the battery-free low-cost reflective balls as position nodes and realize underground target localization with a series of algorithms. In particular, the paper designs a data enhancement strategy based on small-target reorganization to increase the identification accuracy of tiny position nodes. Moreover, a novel ranging algorithm based on multi-filter cooperative denoising has been proposed, and an optimized weighted centroid location algorithm based on multilateral location errors has been designed to minimize underground localization errors. Many experiments in the indoor laboratories and the underground coal mine laboratories have been conducted, and the experimental results have verified that MineBL has good localization performances, with localization errors less than 30 cm in 95% of cases. Therefore, MineBL has great potential to provide a low-cost and effective solution for precise target localization in complex underground environments.
在地下煤矿开采中实现精确定位是煤矿安全生产中的一项具有挑战性的技术。本文提出了一种基于深度图像的低成本无电池定位方案，称为MineBL。其主要思想是利用低成本的无电池反射球作为位置节点，并通过一系列算法实现地下目标定位。具体而言，本文设计了一种基于小目标重组的数据增强策略，以提高微小位置节点的识别精度。此外，还提出了一种基于多滤波器协同去噪的新型测距算法，并设计了一种基于多边定位误差的优化加权质心定位算法，以最小化地下定位误差。在室内实验室和地下煤矿实验室进行了大量实验，实验结果验证了MineBL具有良好的定位性能，在95%的情况下定位误差小于30厘米。因此，MineBL有很大潜力为复杂地下环境中的精确目标定位提供低成本且有效的解决方案。
