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煤矿从业人员不安全状态快速检测系统研究与应用

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为前移煤矿从业人员不安全行为预控关口,及时预警煤矿从业人员人因风险,以红柳林煤矿为工程背景,基于前期研究积累构建的煤矿从业人员不安全状态理论框架,交叉融合多学科优势,以煤矿从业人员生理—心理—行为耦合关联信息解析模型、多源异构数据特征层融合方案、不安全状态的分级方法与预警标准等作为主要技术支撑,研发了由量表数据检测系统、体征数据检测系统、面部生理数据检测系统及岗前不安全状态智能检测系统 4 部分组成的煤矿从业人员不安全状态快速检测系统.现场应用实践结果表明,本系统结构合理、层次清晰、容错性强、出错率低,运行稳定,易于维护,深度契合了国家对煤矿智能化改革的政策和发展趋势,应用前景广阔.
Research and Application of Rapid Detection System for Unsafe States of Coal Mine Workers
In order to advance the pre-control of unsafe behaviors of coal mine personnel and provide timely warnings for hu-man factor risks,in this paper,the Hongliulin coal mine was taking as the engineering background and based on the theoreti-cal framework for the unsafe state of coal mine personnel accumulated in previous researchs,multidisciplinary advantages were integrated.A rapid detection system for unsafe states of coal mine workers consisted of a scale data detection system,a physiological data detection system,a facial physiological data detection system,and a pre-job unsafe state intelligent detec-tion system was developed,which was mainly and technically supported by a physiological-psychological-behavioral cou-pling information analysis model,a feature layer fusion scheme for multi-source heterogeneous data,a grading method for unsafe states,and warning standards.On-site application results show that this system has a reasonable structure,clear hier-archy,strong fault tolerance,low error rate,stable operation,and easy maintenance,deeply aligning with national policies and development trends for the intelligent reform of coal mines,and has broad application prospects.

unsafe statecoal mine workermulti-source data fusionintelligent terminalrapid detection system

常波峰、田水承、李国为、李红霞、苗彦平、田方圆、毛俊睿

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陕煤集团神木红柳林矿业有限公司,陕西 榆林 719313

西安科技大学,陕西 西安 710054

不安全状态 煤矿从业人员 多源数据融合 智能终端 快速检测系统

2024

安全
北京市劳动保护科学研究所 中国职业安全健康协会

安全

影响因子:0.186
ISSN:1002-3631
年,卷(期):2024.45(10)