Equipment exception detection method and device, computer equipment and storage medium

Abstract

The invention discloses an equipment exception detection method and device, computer equipment and a storage medium. The method comprises the following steps of: obtaining a time domain monitoring signal obtained through monitoring equipment; carrying out frequency domain transformation on the time domain monitoring signal so as to obtain a frequency domain monitoring signal; adjusting an amplitude value of each frequency domain component in the frequency domain motoring signal according to a dimensionless processing algorithm; and inputting the frequency domain components, the amplitude values of which are adjusted, in the frequency domain monitoring signal into a pre-trained exception detection model, so as to obtain an exception detection result, wherein the exception detection model learns to obtain a corresponding relationship between the frequency domain components adjusted by adoption of the dimensionless processing algorithm and the exception detection result. The method is capable of realizing real-time and automatic exception detection for mass apparatuses, and enhancing the result detection efficiency and correctness.

Description

technical field [0001] The present invention relates to the technical field of information processing, in particular to an equipment abnormality detection method, device, computer equipment and storage medium. Background technique [0002] With the continuous development and innovation of computer technology, Internet of Things technology has made great progress in many fields. At present, the number of devices connected to the Internet of Things is relatively large. How to manage and monitor the status of each device in real time and detect whether the device is abnormal has very far-reaching significance. [0003] In the prior art, for a sensor whose output signal is a periodic function in the device, the existing abnormal causes are manually summarized, and then according to the frequency spectrum of the sensor output signal, it is judged whether the sensor is abnormal. In this way, by manually judging whether the sensor is abnormal, the efficiency and accuracy are low, ...

AI Technical Summary

Problems solved by technology

[0005] For this reason, the first purpose of the present invention is to propose a device anomaly detection method to realize real-time and automatic anomaly detection of massive equipment, improve the efficiency and accuracy of result detection, and solve the problem of existing manual judgment. Whether the sensor is abnormal, the efficiency and accuracy are low, and the workload is heavy, which is not suitable for technical problems in the detection of massive equipment

Images