The elevator system integrates many types of complex equipment such as mechanical,control and electrical,etc.In order to ensure the safe operation of elevator equipment,it is necessary to effectively identify the risk of safety failures.Based on the elevator acceleration data characteristics,the common elevator faults are diagnosed and analyzed.In order to improve the efficiency of fault monitoring and identification,the time domain analysis method,small packet wave decomposition method and Gaussian mixture model are choosed to use in different types of fault monitoring.The results of the study show that the car acceleration feature mining fault feature identification method has a high accuracy rate and can be widely used in the identification of elevator equipment safety faults.
Elevator carAccelerationFault identificationSafety risk
NETL
NSTL
万方数据
