Research On Hoisting Machinery’s Risk Management Key Technology And System Based On Internet Of Things

As is widely used in various professions of national economy, like metallurgy, ports, electricity, and ocean engineering, hoisting machinery is the backbone of industries. With the rapid developments, transformation and upgrading of international trade, marine energy, shipbuilding industry, and metallurgy industry, all the various situations, like large-scale and complexity, vigorous growths of production scale and equipment ownership, and continuous production safety accidents, have brought up severe challenges for the safety management work of hoisting machinery. Based on this reality, this paper mainly forces on four research tasks:1) Through the comparison analysis of current situations at home and abroad and accident statistics analysis of recent years, this paper summarizes what challenges hoisting machinery safety management works of our country should be faced. Among them, subjectivization of accident cause(more than 70% accidents are caused by unsafe behavior of the people) and man-machine mismatch( with the sustaining 6% growing rate of supervised and inspected personnel, the corresponding rate of the number of equipments is 12%). Hoisting machinery risk management research appears extremely urgent because of both pain points.2) Starting with the demands of hoisting machinery safety management, this paper builds up both micro and macro aspects of risk management system of hoisting machinery: at the micro level, the individual risk management for hoisting machinery is proceeded to satisfied the needs of using units( or enterprises); at the macro level, hoisting machinery regional risk management research is proceeded to enhance the efficiency of safety supervision and inspection.3) This paper carries out the key technique research of single risk assessment method and regional risk classification method, which formed risk estimation index system with two elements, six primary index and some three or four indicators, and regional risk classification method based on the principle of 80/20. The application cases of 878 sets of hoisting machineries in 47 user units at 8 pilot regions are have verified the feasibility of the above methods.4) Hoisting machinery risk management system is designed and developed based on the internet of things. The system is able to realize data collection and processing with efficient paperless and risk information display with intelligent visualization, and good function expansibility because of the structured design. Through 23631 dates of hoisting machineries at 8 pilot regions, it has confirmed the functions of data collection, analysis, display and management in this system have the advantages of high reliability and good adaptability. May limited research and exploring of this paper promote the development of risk management work of hoisting machinery even Special Equipment to some extent.