Equipment anomaly detection method, system and equipment and storage medium

Abstract

The embodiment of the invention provides an equipment anomaly detection method and system, equipment and a storage medium, and the method comprises the steps: carrying out the data collection of target equipment through employing three-light collection equipment within a preset time period, obtaining three-light fusion image sequence data, inputting the data into an anomaly feature extraction model, and carrying out the feature extraction, the method comprises the following steps: acquiring multivariable time sequence data, performing sub-sequence division on partial or all data in the multivariable time sequence data to acquire variable quantum sequence segment data, inputting the variable quantum sequence segment data into a preset anomaly detection model for error judgment, and acquiring an abnormal state judgment result of target equipment. Compared with the prior art, the method has the advantages that the multivariable time sequence data subjected to abnormal feature extraction is subjected to sub-serialization, and on the basis of ensuring the data accuracy, the variable quantum sequence segment data reflecting the equipment abnormity is obtained, so that compared with the prior art, the detection accuracy and the detection efficiency are improved. Therefore, the power equipment anomaly detection efficiency is improved.

Description

technical field [0001] The invention relates to the field of equipment detection, in particular to a method, system, equipment and storage medium for equipment abnormality detection. Background technique [0002] At present, when abnormality detection is performed on electric equipment, the operation and maintenance personnel usually detect the abnormal state of the electric equipment according to the inspection parameters of the electric equipment or light wave observation equipment. Among them, when the operation and maintenance personnel use the light wave observation equipment to detect the abnormal state, they use the light wave observation equipment to detect the infrared light, ultraviolet light or visible light image of the power equipment. [0003] However, the existing technology requires operation and maintenance personnel to carry the above-mentioned three kinds of light wave observation equipment respectively, to collect the image information of the three kinds ...

AI Technical Summary

Problems solved by technology

[0003] However, the existing technology requires operation and maintenance personnel to carry the above-mentioned three kinds of light wave observation equipment respectively, to collect the image information of the three kinds of light wave spectrum segments of the power equipment respectively, and then manually analyze the faults of the three kinds of image information to determine the current power equipment. Whether it is in an abnormal state, and when the features in the image information are not obvious, it is easy to cause misjudgment by manual judgment

This leads to a reduction in the efficiency of the existing technology for abnormal detection of power equipment

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