Real-time detection method for elevator motion abnormities

Abstract

The invention discloses a real-time detection method for elevator motion abnormities. The real-time detection method comprises the following steps that acceleration data and angular velocity data of elevator motion are converted into corresponding frequency domain data through wavelet transformation, data analysis such as threshold analysis bonded with the motion states is conducted on elevator motion data in a frequency domain, and the safety level evaluation result of the elevator motion is obtained in real time; and a threshold in threshold analysis can be adjusted according to the different motion states, and by adjusting parameters of wavelet transformation, the detection method can have different time resolutions and frequency resolutions according to different needs. According to the real-time detection method, an elevator safety evaluation method which is novel in angle, conforms to the actual situation and is high in accuracy and adjustable in resolution is realized, the hardware requirement is low, and portability is high.

Description

technical field [0001] The invention relates to an elevator fault detection technology, in particular to a real-time detection method for abnormal motion of an elevator. Background technique [0002] As far as the current situation of the domestic elevator industry is concerned, there are still many problems in the monitoring of the movement status of the elevator car. Due to the large number of elevators in my country, although the elevator industry is developing steadily, the level of elevator repair and maintenance closely related to it is difficult to keep up with the pace of the industry. This is an important reason for the high frequency of elevator safety accidents in my country. [0003] At present, most elevators in buildings work in an independent and closed environment, and maintenance personnel cannot grasp the working status of elevators in real time and deal with problems arising during elevator operation in a timely manner. Moreover, the country lacks efficie...

AI Technical Summary

Problems solved by technology

[0005] 1) Most of them use the data cabinet in the elevator motor system as the data source, so it depends on the specific elevator type and model, and the portability is poor;

[0006] 2) The fault judgment method is to simply check whether the elevator motion data exceeds a fixed threshold, and the threshold cannot be adjusted according to the different motion states of the elevator, so it cannot be judged in combination with the motion state, and the accuracy is poor;

[0007] 3) The fault judgment method is based on the data analysis of the signal in the time domain, without considering the information provided by the signal in the frequency domain, so the source of information is single and the accuracy is poor

Images