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An electric power defect level identification method based on deep semantic matching

A technology of semantic matching and defect level, applied in the field of level recognition, can solve problems such as inability to consider deep context semantics, lack of interpretability, poor generalization ability, etc., achieve high-precision power defect level identification, and realize power defect level Recognize and improve the effect of grade recognition rate

Active Publication Date: 2019-05-10
ZHOUSHAN ELECTRIC POWER SUPPLY COMPANY OF STATE GRID ZHEJIANG ELECTRIC POWER +1
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Problems solved by technology

[0008] 4) The defect description text has a large amount of data, which is conducive to machine learning to mine the hidden laws in the text, but at the same time, it also puts forward certain requirements for the classification efficiency and storage overhead of the classification model
However, the above traditional methods cannot consider deep contextual semantics, sparse vectors, and lack of interpretability, which lead to low classification accuracy or poor generalization ability.

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  • An electric power defect level identification method based on deep semantic matching
  • An electric power defect level identification method based on deep semantic matching
  • An electric power defect level identification method based on deep semantic matching

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[0037] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings of the description.

[0038] Such as figure 1 As shown, the power defect level recognition method based on deep semantic matching includes the following steps:

[0039] 1) Construct a deep structural semantic model, and use a deep neural network to divide sentences into five layers from bottom to top, including input layer, presentation layer, matching layer, sorting layer and output layer;

[0040] 2) Preprocess the text based on the word hashing and word segmentation model, and construct the input layer. The input layer is the defective text to be classified, and N training set texts. The larger the value of N, the better. Map the sentence into a vector space and Input into DNN; since the power defect text is mixed with Chinese, English letters, and numbers, the processing of these three characters is quite different:

[0041] For E...

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Abstract

The invention discloses an electric power defect level identification method based on deep semantic matching, and relates to the technical field of electric power defect level identification. A traditional text classification model has a vector space model based on Boolean values, the defects that deep context semantics cannot be considered, vectors are sparse, interpretability does not exist andthe like are overcome, and the classification precision is not high for defective texts of power equipment. According to the method, a deep neural network is adopted to divide sentences into five layers of structures including an input layer, a representation layer, a matching layer, a sorting layer and an output layer, and a deep structure semantic model is achieved; then, the text is preprocessed on the input layer based on word hashing and a word segmentation model; on the basis of the deep neural network, an input layer, a representation layer and a matching layer are trained in sequence to obtain a low-dimensional representation vector of the defect text; and finally, obtaining the average defect level of the to-be-classified text based on the semantic similarity of the cosin distanceand the TopK sorting model. The level identification rate of the defect text is effectively improved, and high-precision power defect level identification is realized.

Description

technical field [0001] The invention relates to the technical field of power defect level recognition, in particular to a power defect level recognition method based on deep semantic matching. Background technique [0002] During the daily operation and maintenance of power equipment, it is usually necessary to record the defects of power equipment. The recorded content usually includes the type, name, date of defect discovery, defect description, defect classification, etc., thus forming a large number of power defect texts. Different from other content of the defect record, the defect description is recorded in the form of short text, without a fixed format and structure, but it contains more important defect information, such as the specific part of the device where the defect occurs, the specific phenomenon of the defect, etc., is An important supplement to other defect records, especially for some ambiguous defects, the inspection personnel will record the specific defe...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06F16/35
CPCY04S10/50
Inventor 罗麟位一鸣袁海范邓业杨海波潘巍巍
Owner ZHOUSHAN ELECTRIC POWER SUPPLY COMPANY OF STATE GRID ZHEJIANG ELECTRIC POWER
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