A distribution network equipment state maintenance method based on a big data fusion analysis model

Abstract

The invention discloses distribution network equipment state maintenance based on a big data fusion analysis model. Operation of a device, the use and the environment state are monitored; the currentactual working conditions of a large amount of equipment are taken as the basis; through a state monitoring and diagnosis evaluation means, the state of the equipment is judged, the premature symptomof a fault is identified, a fault part, the severity degree of the fault part and the fault development trend are judged, and according to an analysis and diagnosis result, maintenance is actively carried out before the performance of the equipment is reduced to a certain degree or the fault is about to happen.

Description

technical field [0001] The invention relates to a smart grid technology, in particular to a condition maintenance method for distribution network equipment based on a big data fusion analysis model. Background technique [0002] Maintenance of distribution network equipment is an important measure to ensure its safe and stable operation. A reasonable maintenance plan can not only improve the economic benefits of the power grid enterprise itself, but also ensure the reliability of power supply of the distribution network to the greatest extent. At present, the maintenance methods of equipment mainly include after-event maintenance and preventive maintenance. After-event maintenance refers to the maintenance activities performed to restore the equipment to the specified or initial state after the equipment is faulty. It is also called fault repair. Its activities usually include: fault location, fault isolation, disassembly and replacement of components, assembly, adjustment, ...

AI Technical Summary

Problems solved by technology

It can maximize the use of equipment, but there are major defects in this maintenance method: because the failure time is random, it is impossible to arrange the maintenance time in a planned way, and after-the-fact maintenance will disturb the production operation plan, making the production order passive and possibly Serious damage to equipment, resulting in long repair time and high cost

The feature of preventive maintenance is to determine the maintenance cycle of equipment overhaul and minor repair according to the failure rules of different equipment in advance. To a certain extent, the failure can be eliminated in the bud, but targeted maintenance cannot be achieved.

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