A Data Aided Judgment Method Based on Dynamic Statistics

Abstract

The invention relates to a data-aided judgment method based on dynamic statistics. The method sets the attention threshold interval on the basis of the standard judgment basis for the collected electrification detection data, and specifically includes: a first judgment step of preliminary judgment according to the standard judgment basis A statistical step of performing data statistics on the electrification detection data and setting a caution threshold interval according to the statistical results; a second judgment step of assisting judgment based on the electrification detection data of each device under test and the set attention threshold interval. Compared with the prior art, the present invention has the advantages of high judgment result precision, high reliability of auxiliary judgment and the like.

Description

technical field [0001] The invention relates to a data processing method in the technical field of electrification detection, in particular to a data-assisted judgment method based on dynamic statistics. Background technique [0002] In recent years, with the transformation of power grid equipment maintenance from periodic maintenance to condition-based maintenance, condition detection has been more and more widely used. Live detection is an important branch of state detection. Portable detection instruments are usually used for on-site detection of power grid equipment in the running state, which has the characteristics of flexibility, accuracy, and timeliness. Live detection test data, as an important equipment state characterization parameter, is one of the data sources for power grid equipment state evaluation. [0003] At present, there are still several problems to be solved in the live detection business: First, the data of live detection mainly rely on the manual re...

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Problems solved by technology

[0003] At present, there are still several problems to be solved in the live detection business: First, the data of live detection mainly rely on the manual records of field test professionals. This original method has defects such as poor data standardization and the inability to conveniently archive statistical analysis of measurement results.

Second, there are many types and large quantities of data collected in the field work of live detection. When compiling the analysis report, it needs to go through very cumbersome data collection, sorting and editing. Not only is the work efficiency low, but the accuracy and integrity of the data are also difficult to guarantee.

However, the participation of multiple teams also brings about uneven work process standardization and work product quality, and the management requirements for standardized operations are becoming more and more urgent.

Fourth, although the PMS system has accumulated a large amount of valuable data, it cannot be effectively used in the field work of live detection due to reasons such as site, equipment, and network

[0004] The judgment of the existing live detection data is mostly carried out according to the standard. However, there are certain defects in the actual application. For example, the abnormal judgment in the infrared temperature measurement is as follows: 1. The absolute temperature does not exceed the standard; 2. The relative temperature rise of the ABC three-phase does not exceed the standard.

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