Switch cabinet safety detection method based on big data

Abstract

The invention discloses a switch cabinet safety detection method based on big data. The method comprises the steps of data acquisition, data preprocessing, data reconstruction, detection data clustering processing and switch cabinet safety detection. The invention belongs to the technical field of switch cabinet detection, and particularly relates to a switch cabinet safety detection method based on big data, and the method carries out the data reconstruction of the safety detection data of a switch cabinet through introducing a comparison learning target, and facilitates the precise recognition of the fault type of the switch cabinet. The alignment of potential space of the safety detection data of the switch cabinet is improved through three constraints, so that the safety detection accuracy of the switch cabinet is improved; local density is calculated by introducing multi-scale density and dynamic distance weight, noise point elimination is carried out based on a self-adaptive dynamic threshold value, processing of switch cabinet safety detection data is realized based on gravitation balance state determination, and accurate separation of an abnormal state and a normal state is ensured. And the switch cabinet fault detection and classification efficiency is high.

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