Condition monitoring data cleaning method for power transmission and transformation equipment based on time series analysis

A technology for time series analysis, power transmission and transformation equipment, applied in the direction of electrical digital data processing, data processing applications, special data processing applications, etc.

Active Publication Date: 2017-11-10
STATE GRID CORP OF CHINA +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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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 all discarded during the data cleaning process, resulting in data loss, which is not conducive to the mining of the data itself in the subsequent status assessment.

Method used

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  • Condition monitoring data cleaning method for power transmission and transformation equipment based on time series analysis
  • Condition monitoring data cleaning method for power transmission and transformation equipment based on time series analysis
  • Condition monitoring data cleaning method for power transmission and transformation equipment 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

A time sequence analysis-based state monitoring data cleaning method for a power transmission and transformation device, comprising the steps of: establishing an initial time sequence model for state data of a power transmission and transformation device, and estimating an initially-fit residual sequence and residual variance by means of the initial time sequence model; calculating a test statistic of each observation point utilizing the initial time sequence model; judging whether a maximum value of the absolute values of test statistics is greater than a set threshold value; and calculating the test statistic of each of the observation points by means of a model residual of a corrected time sequence model, and judging whether a new noise point exists according to whether the maximum value of the absolute values of the test statistics is greater than the set threshold value, until all the noise points are identified. The method has the advantages of a high cleaning efficiency, keeping the data integrity, and avoiding the loss of useful information about data.

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...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06Q50/06
CPCG06F16/00
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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