Crowdsensing location method of mining-induced seismicity based on the phone mobile sensor network

LUO Hao; FENG Tian-zhen; YU Jing-kang; PAN Yi-shan; ZHANG Li

doi:10.13374/j.issn2095-9389.2021.06.16.007

Volume 44 Issue 12

Dec. 2022

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Article Navigation > Chinese Journal of Engineering > 2022 > 44(12): 2017-2028

LUO Hao, FENG Tian-zhen, YU Jing-kang, PAN Yi-shan, ZHANG Li. Crowdsensing location method of mining-induced seismicity based on the phone mobile sensor network[J]. Chinese Journal of Engineering, 2022, 44(12): 2017-2028. doi: 10.13374/j.issn2095-9389.2021.06.16.007

Citation:

LUO Hao, FENG Tian-zhen, YU Jing-kang, PAN Yi-shan, ZHANG Li. Crowdsensing location method of mining-induced seismicity based on the phone mobile sensor network[J]. Chinese Journal of Engineering, 2022, 44(12): 2017-2028. doi: 10.13374/j.issn2095-9389.2021.06.16.007

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Crowdsensing location method of mining-induced seismicity based on the phone mobile sensor network

doi: 10.13374/j.issn2095-9389.2021.06.16.007

1.
College of Information, Liaoning University, Shenyang 110036, China
2.
School of Environment, Liaoning University, Shenyang 110036, China

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Corresponding author: E-mail:luohao8711@163.com
Received Date: 2021-06-16
Available Online: 2021-10-21
Publish Date: 2022-12-01

Abstract

Abstract

To improve the positioning accuracy of a mining-induced seismicity monitoring system, reduce the monitoring blind area, and reduce the monitoring cost, based on the distributed idea, this paper proposes a positioning method of mining-induced seismicity based on the smartphone sensor network. First, smartphones used by workers and their families near the mining area were utilized to establish a mobile sensor network. Second, the simulated source points were meshed, and the objective function based on the standard deviation was constructed. An improved firefly optimization strategy was proposed. The inflection point backtracking method and smartphone sensor network exclude the discrete points strategy, namely, EDPS, to reduce the positioning error. Verification is done by the simulation experiment of the mining-induced seismicity location. Experimental results show that under the ideal condition of no arrival time error in the smartphone sensor network, all simulated source points can converge to the source position accurately with a positioning error of less than 1 m. However, compared to the detector, the arrival error of the smartphone is higher, and the positioning error is correlated with the arrival error. When the mobile phone arrival error is ?1.0–1.0 s, the traditional algorithm positioning error is 216 m, which cannot achieve high-accuracy positioning. Researching the relationship between objective function value and positioning error, this work proposes and uses two optimization methods: (1) inflection point backtracking method and (2) EDPS. The absolute positioning error of the algorithm is reduced to 73 m. When the time error is ?0.2–0.2 s, the absolute positioning error is reduced to 17 m, and the positioning accuracy is improved by 76.1%. The location method of the mining-induced seismicity based on the crowdsensing of a phone mobile sensor network provides a new method for mining-induced seismicity monitoring. It can be considered to combine with an underground microseismic system in the future, which is of great significance in saving the monitoring cost and improving the positioning accuracy.
- mining-induced seismicity,
- smart phone,
- group intelligence positioning,
- arrival error,
- exclude discrete points strategy (EDPS)

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References

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