Elevator state detection method and device, electronic equipment and storage medium

By fusing elevator motion characteristics and air pressure data using a Kalman filter model, the problem of high elevator positioning costs was solved, enabling precise positioning and fault early warning, and promoting intelligent elevator management.

CN122301037APending Publication Date: 2026-06-30ZHEJIANG UNIVIEW TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ZHEJIANG UNIVIEW TECH CO LTD
Filing Date
2024-12-27
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing elevator operation monitoring solutions are complex, have high installation and maintenance costs, making them difficult to promote on a large scale. Furthermore, they are challenging to troubleshoot and repair, which hinders the development of intelligent elevator management.

Method used

A target Kalman filter model is used to fuse elevator motion characteristic data and air pressure data. The Kalman filter model is used to predict the elevator's running height and correct for accumulated errors and environmental noise when the elevator is stationary, thus achieving accurate positioning.

Benefits of technology

It reduces elevator positioning costs, improves the accuracy of floor height prediction, supports elevator fault early warning and intuitive display of monitoring information, and promotes intelligent elevator management.

✦ Generated by Eureka AI based on patent content.

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Abstract

This invention provides an elevator status detection method, device, electronic device, and storage medium. The method includes: determining target elevator operating parameter information from the start to the end of operation, including motion characteristic data and air pressure data collected along the elevator's vertical direction during operation; determining the predicted height of the target elevator at the end of operation using a target Kalman filter model based on the target elevator operating parameter information; determining the floor where the target elevator is located at the end of operation based on the predicted height; and correcting the target Kalman filter model for accumulated errors and environmental noise introduced during the elevator's operation when the target elevator is stationary at each floor after operation. This technical solution can predict the height of the target elevator at the end of operation based on a Kalman filter model, thereby achieving accurate floor location.
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