Design and Application of Information Platform for Mine Safety Based on Dual Control Preventive Mechanism
As shallow resources become depleted and the complexity of underground mining increases,the incidence of accidents in underground mines has risen,presenting significant challenges to mine safety management.Concurrently,propelled by national policies and the inexorable trend towards smart mine construction,an information platform focused on risk grading control and hazard identification and management emerges is a novel approach for the establishment of mine safety management systems.Firstly,this paper commences with an exploration of the theoretical framework underpinning the dual-prevention mechanism,emphasizing the critical importance of risk grading control and hazard identification and management in the context of mine safety management.In alignment with the"Classification of Occupational Injuries and Diseases"and the"Requirements for Occupational Health and Safety Management Systems",mining enterprises are required to establish a systematic and standardized risk assessment system,so this study integrates multiple risk identification methodologies,including the Safety Check List(SCL),the Likelihood of Exposure Consequences(LEC)analysis,and the Fault Tree Analysis(FTA).By identifying,classifying,and controlling risks,as well as implementing closed-loop management for hazard identification and rectification,the comprehensiveness and effectiveness of the safety management system are ensured.This article subsequently provides a detailed description of the steps involved in system construction,which include the demarcation of operational units,risk identification,risk grading,risk control,and the critical stages of hazard identification and rectification.The paper delineates the control measures applicable to various risk levels and the closed-loop process for the investigation and management of latent hazards,offering practical guidance for mining enterprises.Concentrating on the engineering context of the Tiaoshuihe phosphorus mine,this study elaborates on the informatization construction of the mine safety dual-control platform.Through a comprehensive analysis of current safety management systems and remote intelligent monitoring facilities in mining operations,several critical issues have been identified,including the insufficient implementation of safety risk control measures and the vague specification of risk responsibility systems.In response to these findings,an information management platform has been developed to meet functional,user,and business requirements.This platform encompasses multiple modules,including system auxiliary management,information dissemination,safety training,risk grading control,and hazard identification.Employing JavaEE technical standards in conjunction with the SpringCloud and Alibaba microservices framework ensures the system's flexibility,efficiency,and scalability.The platform's operational examples illustrate fundamental functionalities such as user authentication,risk assessment,hazard source identification,major risk statistics,and the documentation of hazard information.These functionalities are supported by visual interfaces that facilitate data-driven decision-making processes.Furthermore,the platform's design incorporates considerations such as data access efficiency,development convenience,maintenance simplicity,and system operational security,thereby creating a highly efficient and reliable safety management tool for mining enterprises.In summary,this paper examines the dual-prevention mechanism and system construction for mine safety,as well as its practical application at the Tiaoshuihe Phosphorus Mine.It provides theoretical foundations and practical approaches for improving safety management in the mining industry,with the aim of preventing and reducing accidents.This facilitates the modernization of safety management practices within mining enterprises,safeguards employee lives,and promotes sustainable corporate development through the implementation of a dual-control mechanism.
万方数据
维普
