Elevator fault prediction method based on BP neural network

Abstract

The invention discloses an elevator fault prediction method based on a BP neural network. The method comprises the following steps that 1, real-time data of the movement of an elevator are collected through a sensor set installed on an elevator car; 2, the collected historical data and standard data of the movement of the elevator are preprocessed and characteristic parameters are extracted, wherein a part of the characteristic parameters serves as a data sample, and the other part serves as a test sample; 3, a bp neural network diagnosis model is built, and the collected data sample is inputfor training; and 4, then the test sample is input to the trained bp neural network, the recognition accuracy of the trained sample and the test sample is determined, a training algorithm is optimized, the optimized neural network parameter configuration is used, and the elevator is subjected to fault detection. The elevator fault diagnosis method has the advantages of being high in real-time performance and diagnosis precision, capable of judging whether the elevator has potential safety hazards or not in real time, reducing the cost for manually maintaining the safety of the elevator, and finally achieving the balance of the safety performance and the economic benefit.

Description

technical field [0001] The invention relates to an intelligent elevator safety monitoring technology, in particular to an elevator fault prediction method based on a BP neural network. 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 well, 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 la...

AI Technical Summary

Problems solved by technology

Due to the large number of elevators in my country, although the elevator industry is developing well, the elevator repair and maintenance level closely related to it is difficult to keep up with the pace of the industry. This is an important reason why the frequency of elevator safety accidents in my country remains high.

[0003] At present, most building elevators work in an independent and closed environment, and maintenance personnel cannot grasp the working status of the elevator in real time and deal with problems arising in the operation of the elevator in a timely manner.

Moreover, the country lacks efficient and accurate monitoring technical means and equipment in the elevator monitoring link, and the inspection agency has not yet established a complete remote monitoring network

However, the high-frequency maintenance inspection of the elevator will greatly increase the maintenance cost and bring a great economic burden to the user.

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