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利用可见光的新型矿笼安全监测算法。

A Novel Mine Cage Safety Monitoring Algorithm Utilizing Visible Light.

机构信息

School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.

China Mine Digitization Engineering Research Center, Ministry of Education, Xuzhou 221116, China.

出版信息

Sensors (Basel). 2020 Jul 14;20(14):3920. doi: 10.3390/s20143920.

Abstract

The mine cage has an important role in the production of coal mines. It has many safety problems in the transportation of people, such as overloading of personnel and illegal outreach of human limbs. However, the harsh mine environment makes it very difficult to monitor personnel overload and limb extension. To solve these two problems, we propose a novel safety monitoring algorithm of the mine cage based on visible light. With visible light technology, our algorithm cleverly utilizes the existing underground lighting equipment (i.e., miner's headlamp and the miner's lamp deployed on the mine cage) as the transmitter to broadcast the light beacons representing unique identity information through visible light frequency modulation. Next, cheap photodiodes deployed in the mine cage are used as the receiver to perceive the modulated optical signals. Then we use the frequency matching method for personnel counting and the frequency power comparison method for illegal limb extension monitoring. Moreover, a novel method of monitoring the delineated safe area of the mine cage is also proposed to ensure that all the miners are in the delineated safe area. Finally, we conducted extensive experiments with a simulated mine cage model. Results show that our algorithm has superior performance. With the photodiode SD5421-002, the accuracy of personnel overload judgment and safe area monitoring of our algorithm can reach 99%, and the accuracy of limb extension monitoring is more than 96%.

摘要

罐笼在煤矿生产中起着重要作用。它在人员运输方面存在许多安全问题,例如人员超载和非法伸出肢体。然而,恶劣的矿山环境使得监测人员超载和肢体延伸非常困难。为了解决这两个问题,我们提出了一种基于可见光的新型矿笼安全监测算法。利用可见光技术,我们的算法巧妙地利用现有的地下照明设备(即矿工头灯和安装在矿笼上的矿工灯)作为发射器,通过可见光频率调制广播代表独特身份信息的光信标。接下来,在矿笼中部署廉价的光电二极管作为接收器,以感知调制的光学信号。然后,我们使用频率匹配方法进行人员计数,使用频率功率比较方法进行非法肢体延伸监测。此外,还提出了一种监测矿笼划定安全区域的新方法,以确保所有矿工都在划定的安全区域内。最后,我们使用模拟矿笼模型进行了广泛的实验。结果表明,我们的算法具有优越的性能。使用光电二极管 SD5421-002,我们算法的人员超载判断和安全区域监测的准确率可达 99%,肢体延伸监测的准确率超过 96%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3390/7412026/fd12007dc5d3/sensors-20-03920-g001.jpg

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