Electric-transmission-and-transformation-equipment state monitoring data cleaning method based on time series analysis

A technology of time series analysis and power transmission and transformation equipment, which is applied in the direction of electric digital data processing, data processing applications, special data processing applications, etc., and can solve problems such as data loss, unfavorable mining, and damage to the continuity of state quantity data chains.

Active Publication Date: 2015-04-22
STATE GRID CORP OF CHINA +1
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Problems solved by technology

However, this clustering method directly eliminates the separated noise data, which destroys the continuity of the state quantity data chain.
The above studies were

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  • Electric-transmission-and-transformation-equipment state monitoring data cleaning method based on time series analysis
  • Electric-transmission-and-transformation-equipment state monitoring data cleaning method based on time series analysis
  • Electric-transmission-and-transformation-equipment state monitoring data cleaning method based on time series analysis

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Embodiment Construction

[0082] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0083] The principle of the present invention is to use the time series model to identify the time series of each state quantity, and select different correction formulas according to the types of noise points in the sequence, so as to achieve the purpose of correcting noise point data and filling missing values, and complete the data cleaning of state quantities . This method can not only identify noise points and missing values ​​in the data, but also correct the value of noise points in the process of separating noise. Its overall process is as follows figure 1 shown.

[0084] The detection of the state quantity of power transmission and transformation equipment is completed by various sensors, but the raw data uploaded to the database for state evaluation after the underlying preprocessing can be considered as feature quantity data arranged in tim...

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Abstract

The invention discloses an electric-transmission-and-transformation-equipment state monitoring data cleaning method based on time series analysis. The electric-transmission-and-transformation-equipment state monitoring data cleaning method includes the following steps: building an initial time series model of state data of electric transmission and transformation equipment, and estimating an initially-fit residual series and an initially-fit residual variance through the initial time series model; calculating the test statistics amounts of observing points through the initial time series model; judging whether the maximum value of the absolute values of the test statistics amounts is larger than a threshold value or not; calculating the test statistics amounts of the observing points through the modified model residual of the time series model, and judging whether new noise points exist or not by judging whether the maximum value of the absolute values of the test statistics amounts is larger than the threshold value or not till all the noise points are identified. The electric-transmission-and-transformation-equipment state monitoring data cleaning method has the advantages that the cleaning efficiency is high, the data integrity is kept, and the useful information of data is prevented from being lost.

Description

technical field [0001] The invention relates to a method for cleaning state monitoring data of power transmission and transformation equipment based on time series analysis. Background technique [0002] It is the development trend of equipment status evaluation and diagnosis technology to conduct all-round analysis of equipment panoramic status information such as equipment online monitoring, live detection, and offline test, and improve the accuracy of power transmission and transformation equipment evaluation and abnormal diagnosis. The panoramic status information of power transmission and transformation equipment presents the characteristics of multiple sources, heterogeneous information, huge quantity, and various attributes, and its data is often incomplete, noisy, and inconsistent. The original data quality of the state quantity often cannot meet the requirements of the subsequent state evaluation model, so data cleaning is essential before state evaluation or diagno...

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Application Information

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IPC IPC(8): G06F17/30G06Q50/06
CPCG06F16/00G06Q50/06
Inventor 郭志红杜修明杨祎陈玉峰盛戈皞严英杰
Owner STATE GRID CORP OF CHINA
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