Intelligent Assistant Disposal System for Monitoring Defects Based on Big Data Analysis Technology

Abstract

The invention discloses a monitoring defect intelligent auxiliary disposal system based on a big data analysis technology, which comprises a monitoring defect information detection and identificationmodule, a monitoring defect intelligent judgment module, a typical defect signal expert analysis knowledge base, a monitoring defect auxiliary disposal module and a defect disposal situation automatictracking module; wherein the monitoring defect information detection and identification module and the typical defect signal expert analysis knowledge base are connected with the monitoring defect intelligent judgment module, the monitoring defect information detection and identification module transmit defects detection information to the monitoring defect intelligent judgment module, the typical defect signal expert analysis knowledge base exchanges information with the monitoring defect intelligent judgement module, the monitoring defect auxiliary disposal module is connected with the monitoring defect intelligent judgement module, and the defect disposal status automatic tracking module is connected with the monitoring defect auxiliary disposal module. The invention timely finds out and eliminates the unsafe factors affecting the stable operation of the electric power system, eliminates the defects in the budding state, and ensures the safe operation of the electric network.

Description

technical field [0001] The invention relates to substation equipment defect monitoring, identification, judgment, and disposal, in particular to an intelligent auxiliary disposal system for monitoring defects based on big data analysis technology, which belongs to the technical field of electric power equipment. Background technique [0002] Defects in substation equipment are a major hidden danger to the safe and stable operation of the power grid. Timely and accurate detection and disposal of equipment defects in unattended substations is an important prerequisite for ensuring the safe and stable operation of power grid equipment. At present, the monitoring, identification, judgment, disposal, and recording of equipment defects are all done manually. The following problems exist in relying solely on manual labor: important signals may be missed during the identification process, misjudgments may be misjudged during the judgment process, and there may be problems during the ...

AI Technical Summary

Problems solved by technology

At present, the monitoring, identification, judgment, disposal, and recording of equipment defects are all done manually. The following problems exist in relying solely on manual labor: important signals may be missed during the identification process, misjudgments may be misjudged during the judgment process, and there may be problems during the disposal process. It will be handled imperfectly, and the defect record may be overdue and not closed, etc.

The traditional manual monitoring and identification processing mode of equipment defects needs to be transformed into an active real-time perception and standard intelligent disposal mode, so as to timely discover and eliminate unsafe factors affecting the stable operation of the power system, eliminate defects in the bud, and ensure safe operation of the power grid

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