Recent advances in research on underground space positioning technology for coal mining
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Abstract
Efficient coal mining is essential for ensuring China’s energy security, and the advancement toward intelligent coal mining represents a strategic move to foster high-quality development within the coal industry. The cornerstone of realizing intelligent coal mines lies in underground space positioning technology. Accurate positioning is crucial not only for safeguarding miner safety but also for optimizing mining operations, improving equipment utilization and minimizing operational costs. The unique challenges of underground mining, such as the absence of satellite navigation signals, restricted and confined operating environments, and harsh electromagnetic and lighting conditions, place new requirements on positioning techniques. This paper focuses on the localization issues specific to underground coal mines, offering a systematic overview of four fundamental localization techniques: range intersection, database matching, dead reckoning, and multisource information fusion. Range intersection determines location by utilizing distance measurements obtained through various methods. Database matching employs online measurements to match against characteristics stored in a database. Dead reckoning calculates the current location by integrating measurements over time. Lastly, multisource information fusion enhances positioning accuracy by combining data from multiple sources. The paper further reviews detailed implementation schemes of these four positioning technologies in coal mines, highlighting typical sensors or systems and summarizing current research developments. For range intersection methods, methods such as visible light, ultrasonic, wireless local area network, bluetooth, ultra-wideband, and infrared positioning are examined. Database matching positioning methods include geomagnetic, gravity, and radio fingerprint positioning systems. Dead reckoning techniques cover inertial navigation, pedestrian navigation, and odometers, while multisource information fusion focuses on integrated navigation and simultaneous localization and mapping. Moreover, the paper identifies key challenges confronting underground positioning systems in coal mines. These challenges encompass the increasing inaccuracies in absolute localization methods, difficulties in correcting dead reckoning localizations, performance declines in multisource fusion localization methods, and the absence of comprehensive standardization. Given the complex environment of coal mines, there is still much room for improving the accuracy and reliability of underground positioning. To address these challenges, this paper proposes several avenues for improvement. Enhancing the performance of the positioning systems might involve fostering collaboration across multiple systems, incorporating brain-inspired navigation to explore new localization solutions, and strengthening seamless and emergency localization capabilities. Furthermore, in today’s interconnected intelligent age, the privacy and security aspects of positioning systems warrant careful consideration.
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