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Soft measurement modeling method based on cooperative noise allocation

A modeling method and soft measurement technology, applied in neural learning methods, biological neural network models, special data processing applications, etc.

Active Publication Date: 2021-10-01
NORTHWEST NORMAL UNIVERSITY
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Problems solved by technology

[0003] Soft sensor modeling is of great significance in industrial process control. Data noise cannot be completely removed, but traditional noise processing methods can only deal with specific noises. Therefore, a new noise processing method is needed to realize noise data and non-noise data. to improve the predictive performance of the model

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  • Soft measurement modeling method based on cooperative noise allocation
  • Soft measurement modeling method based on cooperative noise allocation
  • Soft measurement modeling method based on cooperative noise allocation

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Embodiment Construction

[0035] The present invention will be further described below in conjunction with the accompanying drawings.

[0036] The main function of cooperative apportionment noise operation is to weaken the noise in the data and balance the noise data and non-noise data. Therefore, normal feature extraction and regression network models can be connected after the apportioned noise operation, such as fully connected neural network, convolutional neural network, and recurrent neural network. The model diagram is as follows figure 1 shown.

[0037] In the process of industrial production, due to the complex environment and the large number and types of equipment, the collected data contains a lot of complex noise. The complex noise can be determined and weakened by the characteristics of the data itself, and different attributes have different credibility, and should have different strengths of weakening. The specific collaborative noise sharing operation process is as follows: figure ...

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Abstract

The invention provides a noise weakening method based on cooperative allocation in soft measurement modeling, and realizes a soft measurement modeling instance based on the method. According to the noise weakening method, a credibility vector is constructed by using a correlation coefficient between auxiliary data and a key variable, an offset vector of each data row is constructed by using an Euclidean distance between each data row and sample space center point data, and a real deviation matrix and a deviation direction of each data are constructed by using a difference value between each data and the sample center point data; and finally, the credibility, the offset degree, the deviation and the intensity factors are combined to perform cooperative noise allocation on the original auxiliary data, and different intensity factors are utilized to find the highest point of performance improvement of the model during noise weakening, so that noise data and non-noise data in the collected industrial data are balanced, the problem that noise in soft measurement modeling data is complex is solved, the noise processing difficulty is reduced, the prediction performance of the soft measurement model is improved, and an implemented soft measurement modeling example shows that the method has high adaptability and stability.

Description

technical field [0001] The patent of the present invention relates to a noise processing method and a soft sensor modeling method. It has important application and promotion value in the field of industrial production. Background technique [0002] Industrial processes are complex and changeable, with various indicators, and many indicators are difficult to measure directly with testing instruments, or even impossible to measure. For such indicators, soft-sensing technology is widely used for research and testing at home and abroad. Soft-sensing technology is to construct a mathematical model that uses easily measurable process variables as input and unmeasurable or difficult-to-measure key variables as output. By inferring and estimating key variables, the purpose of replacing hardware functions with software is achieved. In soft sensor modeling, not only the high dimensionality, strong correlation, high redundancy, nonlinearity and complex noise of the data need to be con...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20G06N3/04G06N3/08
CPCG06F30/20G06N3/08G06N3/045
Inventor 高世伟张青松马忠彧田冉刘颜星仇素龙许金鹏
Owner NORTHWEST NORMAL UNIVERSITY
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