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A completion method and a completion device for industrial monitoring data loss

A technology for monitoring data and industry, applied in the direction of electrical digital data processing, special data processing applications, digital data information retrieval, etc., can solve the problem of poor filling effect of data sets, achieve the effect of improving accuracy and reducing noise

Active Publication Date: 2019-05-28
UNIV OF SCI & TECH BEIJING +1
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AI Technical Summary

Problems solved by technology

[0010] The technical problem to be solved by the present invention is to provide a complementing method and a complementing device for missing industrial monitoring data, so as to solve the problem in the prior art that the low-dimensional discrete completely random missing data set with high missing rate has poor filling effect The problem

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  • A completion method and a completion device for industrial monitoring data loss
  • A completion method and a completion device for industrial monitoring data loss
  • A completion method and a completion device for industrial monitoring data loss

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Embodiment 1

[0067] Such as figure 1 and figure 2 As shown, the complementary method for the lack of industrial monitoring data provided by the embodiment of the present invention includes:

[0068] Step 1, obtaining an original data set, wherein the original data set is an original industrial monitoring data set whose missing type is completely random missing;

[0069] Step 2. Construct an autoencoder based on the acquired original data set; when constructing the autoencoder, add noise to the input raw data to train the autoencoder, and the trained autoencoder is used to realize the original data The dimensionality enhancement and dimensionality reduction of the eigenvectors in

[0070] Step 3, build a generative model based on the acquired original data set;

[0071] Step 4: Combine the built autoencoder with the generative model, use the original data set to optimize the training of the combined model, and obtain generated data similar to the feature distribution of the original dat...

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Abstract

The invention provides a complementing method and a complementing device for industrial monitoring data loss, which can improve the data complementing effect. The method comprises the steps of obtaining an original data set, wherein the original data set is an original industrial monitoring data set with the missing type being completely random missing; constructing an automatic coding machine according to the obtained original data set, wherein when the automatic coding machine is constructed, noise is added into input original data, then the automatic coding machine is trained, and the trained automatic coding machine is used for achieving dimensionality increase and dimensionality reduction of feature vectors in the original data; establishing a generative model according to the obtained original data set; and combining the constructed automatic coding machine with the generative model, and carrying out optimization training on the combined model by utilizing the original data set to obtain generated data similar to the original data feature distribution. The invention relates to the field of industrial production and data mining.

Description

technical field [0001] The invention relates to the fields of industrial production and data mining, in particular to a complementing method and a complementing device for missing industrial monitoring data. Background technique [0002] In the industrial field, people pay more and more attention to the value of data, and machine learning and data mining methods are usually used to obtain rules and information from data. The core factor for the success of data mining projects is the quality of the data set. If the quality of the data set is poor or not strongly related to the research problem, no matter how advanced the method of feature selection and model building is, it will not be able to achieve the expected results. [0003] Missing data is a common problem faced by industrial monitoring data. The main reasons for missing data can include: [0004] (a) The working state of the instrument is unstable: on-site environmental factors or human factors cause some instrument...

Claims

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Application Information

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IPC IPC(8): G06F16/215G06N3/04
Inventor 班晓娟刘婷袁兆麟王贻明王青海赵占斌
Owner UNIV OF SCI & TECH BEIJING
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