Transformer substation-oriented machine learning-based semantic labeling method

A machine learning and semantic annotation technology, applied in the field of semantic annotation, can solve the problems of low availability, insufficient timeliness, and low reliability, and achieve the effect of narrowing the gap, facilitating analysis and interpretation, and quickly indexing

Active Publication Date: 2018-04-20
WUHAN NARI LIABILITY OF STATE GRID ELECTRIC POWER RES INST +2
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Problems solved by technology

[0002] In the operation and maintenance business of electric power, the completeness and correctness of live detection data largely depend on the professional level of on-site test personnel, and the reliability is not high; due to the variety of live detection instruments and different standards, there are data inconsistencies. Specifications, availability of low efficiency; equipment status data mainly rely on manual sorting, analysis and application, lack of timeliness

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  • Transformer substation-oriented machine learning-based semantic labeling method
  • Transformer substation-oriented machine learning-based semantic labeling method
  • Transformer substation-oriented machine learning-based semantic labeling method

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Embodiment Construction

[0046]In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0047] At first, introduce the method principle of the present invention, the present invention mainly comprises:

[0048] (1) Collect various documents and materials related to power transmission and transformation state detection, go to the site to collect data, and understand the original format and basic characteristics of various types of data. .

[0049] (2) Carry out hierarchical classification and arrangement according to equipment, detection type, detection item, and data type (numeric type, map type, image and video, etc.).

[0050] (3) Preprocessi...

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Abstract

The invention discloses a transformer substation-oriented machine learning-based semantic labeling method. The method comprises the following steps of: extracting features of a training video and a test image; clustering the features; associating and quantifying generated visual words; carrying out learning by a machine model according to the video and the image after feature description; and labeling a test video and a picture by using a semi-supervised or weak-supervised learning method. According to the method, field operation standardization and data standardization can be realized, data and analysis algorithm sharing between a field side and a center side is realized, the data analysis ability of the field side is improved, the long-distance control and real-time technology support abilities of field operation and maintenance are strengthened, the professionalization and intelligence levels of the field operation and maintenance are improved, the inspection working efficiency andequipment state control ability are enhanced, and the condition based maintenance and aid decision making are strengthened.

Description

technical field [0001] The invention relates to a semantic tagging technology, in particular to an image and video tagging technology based on sparse coding and machine learning. Background technique [0002] In the operation and maintenance business of electric power, the completeness and correctness of live detection data largely depend on the professional level of on-site test personnel, and the reliability is not high; due to the variety of live detection instruments and different standards, there are data inconsistencies. It is standardized and can be used in low-efficiency situations; equipment status data mainly relies on manual sorting, analysis and application, and the timeliness is insufficient. Contents of the invention [0003] The purpose of the present invention is to realize on-site operation standardization and data standardization, realize mutual sharing of data and analysis algorithms between the on-site side and the center side, improve the data analysis...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/62G06K9/66G06K9/72G06Q10/00G06Q50/06
CPCG06Q10/20G06Q50/06G06V10/462G06V30/194G06V30/274G06F18/214
Inventor 杜振波江翼刘正阳聂德鑫冯振新徐进霞朱诗沁梁明辉程林赵坤张杰刘熙丁国成陈庆涛杨海涛吴兴旺尹睿涵
Owner WUHAN NARI LIABILITY OF STATE GRID ELECTRIC POWER RES INST
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