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A Novel Mine Cage Safety Monitoring Algorithm Utilizing Visible Light.
Yang, Xu; Pang, Mingzhi; Li, Peihao; Chen, Pengpeng; Niu, Qiang.
Afiliação
  • Yang X; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Pang M; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Li P; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Chen P; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Niu Q; China Mine Digitization Engineering Research Center, Ministry of Education, Xuzhou 221116, China.
Sensors (Basel) ; 20(14)2020 Jul 14.
Article em En | MEDLINE | ID: mdl-32674499
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%.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Saúde Ocupacional / Minas de Carvão / Extremidades / Monitorização Fisiológica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Saúde Ocupacional / Minas de Carvão / Extremidades / Monitorização Fisiológica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China