Elevator Safety Evaluation And Management In M City

With the further expansion of China’s urbanization and the rapid development of the real estate industry,in recent years,the number of elevators shows a trend of high-speed growth year by year,with the synchronous growth of old elevators with long service life,as well as the continuous growth of many elevator failures and accidents.Although the accident rate of ten thousand elevators in China has been decreasing,the public opinion caused by elevator accidents has continued to rise.In order to provide public safety,the State Administration for Market Regulation has repeatedly proposed to give full play to the role of regulatory agencies,make rational use of new technologies to effectively reduce elevator accidents,and promote the supervision of users and maintenance units.Although the Internet of things has been established in some areas,the new technology and traditional elevator safety evaluation have not been effectively combined,which greatly restricts the active role of big data technology.How to find out useful data from the Internet of things and apply it to the safety management of elevators is particularly necessary.The main contents of this thesis are as follows:1)Through the mathematical statistics and analysis of elevator accidents in recent years,this thesis finds out the different accident forms and causes of elevator accidents,confirms that falling and squeezing are the main types of elevator accidents,and analyzes the causes of elevator accidents from three aspects of human factors,equipment status and management factors.2)Taking the unexpected movement of traction driven elevator as an example,the sequence of important coefficients of each event structure in the fault tree is found out by using the fault tree.Based on the results of the fault tree analysis,the specific measures to prevent elevator accidents are proposed.3)After extracting the dynamic data of elevator operation in the Internet of things,the main fault types of traction drive elevator are found out through statistical analysis.By using the mathematical method of fuzzy hierarchy,the correlation between the fault rate and the potential safety hazard is found out,and the risk level that different faults may cause accidents is clarified.In view of the limitations of existing elevator safety evaluation methods,the fault rate correction system is cited A new model of elevator safety evaluation method is established.The purpose of this paper is to summarize the potential rule,cause mechanism,fault logic and root cause of the fault through accident statistics and analysis of elevator dynamic operation parameters of the Internet of things,carry out classified management of elevator operation safety,make full use of the opportunity brought by new technologies such as big data to elevator management,and establish a safety evaluation method for the analysis of a city’s Internet of things system,The establishment of security management mode can also be transferred to the security management of other cities.