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Transformer defect evaluation method based on big data analysis

A transformer and big data technology, applied in the field of substation inspection, can solve problems such as affecting processing efficiency, and achieve the effect of saving labor, improving efficiency, and realizing lean management.

Inactive Publication Date: 2019-12-13
ELECTRIC POWER RES INST OF GUANGXI POWER GRID CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Defect prediction and quality analysis and evaluation of transformers rely on manual analysis, which greatly affects processing efficiency

Method used

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  • Transformer defect evaluation method based on big data analysis
  • Transformer defect evaluation method based on big data analysis
  • Transformer defect evaluation method based on big data analysis

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Embodiment Construction

[0042] In order to better understand the present invention, the present invention will be further described below in conjunction with accompanying drawing and specific embodiment:

[0043] Such as figure 1 As shown, a transformer defect assessment method based on big data analysis includes the following steps:

[0044] S1: Data collection: collect massive quasi-real-time data service platform, geographic information system, meteorological data, centralized control substation system, video surveillance system, asset management system, centralized control management master station data; the time span of data collection is 1 year.

[0045] S2: Data preprocessing: There are problems such as inconsistency in field description, non-corresponding coding rules, and missing data fields in the data of each system. By formulating verification rules such as data quality and integrity, standardized processing is performed; specifically, the collected data is deduplicated. processing, outl...

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Abstract

The invention belongs to the technical field of substation inspection, and particularly relates to a transformer defect assessment method based on big data analysis, which comprises the following specific steps: S1, collecting data; S2, preprocessing the data; S3, mining the data set, and establishing a defect feature vector; and S4, constructing a substation transformer defect trend evaluation model based on an XGBoost algorithm, and evaluating the operation health degree of the transformer according to the defect characteristics. By the adoption of the method, the substation equipment inspection data value can be fully mined, automatic defect judgment is achieved through equipment health degree scoring, more than 90% of labor can be saved, the efficiency is improved by more than 10 times, and substation inspection and maintenance work is changed into data driving from experience judgment, into state inspection from planned maintenance, into pre-event active prevention from post-eventpassive processing, lean management of operation equipment is achieved, and value-added service is provided for transformer substation inspection work.

Description

technical field [0001] The invention belongs to the technical field of transformer substation inspection, and in particular relates to a transformer defect evaluation method based on big data analysis. Background technique [0002] With the development of unattended substations, substations adopt a variety of intelligent inspection methods, such as: robot inspection, drone inspection, high-definition video monitoring and other inspection and monitoring methods. However, each system did not predict the trend based on the periodic evaluation results, and could not diagnose the abnormal quality of the transformer, and the defect risk could not be eliminated in time. The transformer rotation scheme often relies on a fixed cycle, which is easy to cause waste of resources. Historical inspection data has not been fully mined, and the value of massive data in various systems has not been effectively utilized. The defect prediction and quality analysis and evaluation of transformer...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06K9/62G06Q10/06G06Q50/06
CPCG06F16/2465G06Q10/06395G06Q50/06G06F18/214
Inventor 邬蓉蓉黎大健焦健张炜陈荭谢植飚兰依陈炜智
Owner ELECTRIC POWER RES INST OF GUANGXI POWER GRID CO LTD
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