Method and system for abnormal detection of elevator operating environment based on multivariate analysis

Abstract

The present invention relates to a multivariate analysis-based elevator operating environment abnormality detection method and detection system. The detection method includes: S1. Using a data acquisition module to acquire sensor terminal data and external metadata for monitoring the elevator operating environment, Wherein the external metadata includes weather history data and weather forecast data; S2. Using a data preprocessing module to preprocess the sensor terminal data and the external metadata; S3. Based on the historical sensor terminal data and The external metadata is trained offline on the detection model module to perform offline training to obtain a detection model; S4. Based on the detection model and collecting the current sensor terminal data and the weather forecast data, an online real-time alarm module is used for abnormal detection . The invention has low setting cost and high detection effectiveness.

Description

technical field [0001] The invention relates to the technical field of elevator safety operation monitoring, in particular to a multivariate analysis-based abnormality detection method and detection system for an elevator operating environment. Background technique [0002] In recent years, with the introduction of a series of policies such as urbanization, old building renovation, and elevator installation, the number of urban elevators has increased day by day, and has become an indispensable means of transportation in modern urban buildings, bringing greater convenience to people's travel. But at the same time, the safety guarantee of elevator operation is gradually being challenged, and accidents of safety casualties occur from time to time. Among them, the abnormal operation of the elevator is not monitored in time, and the elevator safety is a major hidden danger for a long time. [0003] At present, with the iteration of basic equipment technology, online monitoring ...

AI Technical Summary

Problems solved by technology

However, among these technologies, on the one hand, the detection method technology is relatively traditional and the accuracy is not enough. For example, a temperature and humidity sensor detection module is installed in the car. When the temperature and humidity exceed the preset rule threshold, the operation will be stopped in time and the environment will be monitored. Troubleshoot

However, this detection method cannot reflect the parameters of other environments, and the coverage is not good, resulting in insufficient accuracy

On the other hand, it is expensive to install more sensors

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