Intelligent mining helmet control method based on fusion of human body information and environmental information

Abstract

The invention discloses an intelligent mining helmet control method based on the fusion of human body information and environmental information, including the acquisition of original brain wave signals; the preprocessing of original brain wave signals; the wavelet decomposition and reconstruction of original brain wave signals; and the characteristics of brain wave signals Extraction; artificial fish swarm algorithm optimizes BP neural network to identify fatigue features; identifies miners' fatigue, monitors miners' environmental information, and performs alarm operations for dangerous situations. The present invention extracts four sub-band energies, ApEn approximate entropy, KC complexity and C 0 The complexity is used as the input layer of the artificial fish swarm algorithm to optimize the BP neural network, and the artificial fish swarm algorithm is trained to optimize the BP neural network to identify miner fatigue, with high recognition accuracy, and through the smart wearable bracelet worn on the miner's wrist, different danger levels Triple alarm in three ways: sound, light and vibration, so as to improve the safety factor of underground operations.

Description

technical field [0001] The invention relates to the technical field of miner fatigue recognition, in particular to an intelligent mining helmet control method based on fusion of human body information and environmental information. Background technique [0002] my country is the largest coal-producing country in the world. On the basis of the technical background of existing mines, traditional mining helmets can no longer meet market demand, so it is necessary to combine digital mine monitoring systems to intelligently upgrade mining helmets. The study of mining smart helmets can complete the monitoring and early warning of complex underground environments, and at the same time provide mining tool body information for the monitoring room on the well, and provide reliable data for accident elimination, rescue and accident cause analysis. The existing mining helmet monitoring system is as follows: [0003] 1. Most of the mine alarm methods are installed in the roadway for so...

AI Technical Summary

Problems solved by technology

[0003] 1. Most of the mine alarm methods are installed in the roadway for sound and light alarm. For those who deviate from the alarm source (such as in the environment of ultra-noise and dust in the excavation line), there are situations such as not receiving the alarm information in time, that is, The timeliness of information cannot be guaranteed

[0004] 2. Underground sensors in coal mines often monitor environmental information at a fixed position. When personnel walk through this position, they cannot understand the information of their own environment, etc., and there are potential safety hazards

[0005] 3. Most of the existing mining helmets only complete the monitoring of the environment where the miners live, voice calls, etc., and basically do not monitor the miners themselves, let alone the detection and evaluation of the fatigue of the miners.

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