Intelligent fault detection method for acquisition operation and maintenance system

Abstract

The invention relates to an intelligent fault detection method for an acquisition operation and maintenance system. Data mining and analysis of the acquisition data of the acquisition operation and maintenance system is carried out, and the fault detection of acquisition equipment is carried out based on a Gaussian kernel density local outlier factor algorithm. The collection operation and maintenance system intelligent fault detection method comprises the steps of feature extraction, principal component analysis, local outlier factor calculation and the like. The method comprises the steps: feature extraction is performed on collected operation and maintenance system data; each intelligent collection device is mapped to a two-dimensional plane through principal component analysis, data visualization is achieved, local outlier factors are convenient to calculate, then the local outlier factors of each intelligent collection device are calculated on the basis of a Gaussian kernel density local outlier factor algorithm, and finally suspected fault probability sorting of all the intelligent collection devices is output. The method is less influenced by local data distribution, is suitable for the condition that a data set lacks training samples, provides reference for acquisition, operation and maintenance detection of an electric power company, improves the hit rate of field inspection, can save a large amount of manpower and material resources, and has great economic benefits.

Description

technical field [0001] The invention relates to the fields of fault detection of intelligent collection equipment and big data mining and analysis, and specifically describes an intelligent fault detection method of a collection operation and maintenance system based on massive collection and operation and maintenance data mining. Background technique [0002] Electric energy information collection is an important part of building a smart grid. Electric energy information collection is the basis for two-way interaction between the power grid and customers, and it undertakes the important tasks of electricity consumption information collection, efficient sharing and real-time monitoring. Provides basic data and information for billing, business, and customer service, forming a closed-loop management of the entire smart electricity consumption; provides technical means for realizing ladder electricity prices or time-of-use electricity prices, and is the embodiment of the count...

AI Technical Summary

Problems solved by technology

However, with the advancement of the application process of electric energy information collection and the improvement of the overall operation quality, the content of operation and maintenance work has also expanded, and the depth of application has continued to deepen. The workload of operation and maintenance has remained high. Difficult to reconcile contradictions between the outdated operation and maintenance work models are gradually emerging

The operation and maintenance work of electric energy information collection is important and complicated. In addition to the application system itself, its monitoring objects also include a large number of field devices such as remote channels, local channels, and collection equipment. These devices are not only huge in number, but also vulnerable to weather, environment, etc. The influence of many factors

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