Big data analysis method based on intermittent faults

Abstract

The invention discloses a big data analysis method based on intermittent faults, belonging to the technical field of electric equipment. In the prior art, the judgment of abnormal urgency mainly relies on human experience and subjective estimation to dispatch orders. This method is very unscientific and random, which leads to waste of dispatched workers and delays normal dispatched workers. Currently, there is a lack of A scientific, reasonable and accurate big data analysis solution. In the present invention, firstly, the influencing factors of abnormal urgency of collection are determined, and the influencing factors include intermittent faults. The data includes on-site collection data and work order flow data, and then performs fluctuation analysis on the electricity consumption of a large number of users. Analyze the influencing factors and establish a model, systematize, hierarchical, and simplify complex issues, provide a practical technical solution, identify and distinguish influencing factors, and include those that have an impact on the urgency into the urgency calculation model, otherwise, Not included, to avoid the waste of dispatched workers.

Description

technical field [0001] The invention relates to a big data analysis method based on intermittent faults, belonging to the technical field of electric power equipment. Background technique [0002] At present, nationwide, the failures caused by the power collection system basically exceed the local operation and maintenance forces. Local bureaus also assess the total efficiency of the normal working equipment of the collection system within the scope of their management, and cannot guarantee that all equipment can be effectively collected. data. At present, the system operation and maintenance work management is in the extensive stage, and there are unreasonable use of resources, and it is impossible to quickly and accurately determine the urgency of each abnormal point, resulting in some urgent abnormal situations that cannot be resolved in time, and more serious situations occur. Judgment of abnormal urgency mainly relies on human experience and subjective estimation to di...

AI Technical Summary

Problems solved by technology

In the actual operation and maintenance process, after some faults are dispatched, the faults will automatically recover after a period of time, resulting in a waste of dispatched labor and delaying normal dispatching. Now there is a lack of a scientific, reasonable and accurate big data analysis solution

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