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Industrial process soft measuring method based on integrated type independent element regression model

A regression model and industrial process technology, applied in electrical testing/monitoring, testing/monitoring control systems, instruments, etc., can solve problems such as unsatisfactory prediction accuracy

Active Publication Date: 2016-11-09
NINGBO UNIV
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Problems solved by technology

[0004] On the other hand, considering the diversity and complexity of actual production objects, choosing a fixed single non-quadratic function to establish the corresponding modified independent element regression (MICR) model can often achieve unsatisfactory prediction accuracy

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  • Industrial process soft measuring method based on integrated type independent element regression model
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  • Industrial process soft measuring method based on integrated type independent element regression model

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Embodiment Construction

[0042] Below in conjunction with shown in Fig. 1, the present invention is described in further detail: the present invention relates to a kind of industrial process soft-sensing method based on integrated independent meta-regression model, and the specific implementation steps of the present invention are as follows:

[0043] Step 1: Use the distributed control system to collect easily measurable data in the industrial production process to form the input training data matrix X∈R of the soft sensor model n×m , and standardize it so that the mean of each process variable is 0 and the standard deviation is 1, and the new data matrix is ​​obtained

[0044] Step 2: Obtain the product composition or quality data corresponding to the input training data X by means of offline analysis to form the output training data Y∈R n×1 , and standardize it so that the mean of each process variable is 0 and the standard deviation is 1, and the new data matrix is ​​obtained

[0045] Step 3:...

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Abstract

The invention relates to an industrial process soft measuring method based on an integrated type independent element regression model, and is used for non-Gaussianity industrial process data. A conventional non-Gaussianity soft measuring regression modeling method requires selection of a non-quadratic function to measure non-Gaussianity, but different industrial process data or objects can cause a fact that enough experiential knowledge for guiding the selection of the non-quadratic function is hard to acquire in an actual application. The method provided by the invention is advantageous in that different soft measuring models are acquired by comprehensively and fully using different non-quadratic functions for training, and the problem of the selection of the non-quadratic function is effectively prevented; a final prediction result is acquired by accumulating weighting coefficients, and then prediction precision of a corresponding soft measuring model is not affected by the selection of the non-quadratic function. The prediction effect of the soft measuring model is greatly improved, and therefore key indexes or quality indexes during the process can be accurately and reliably predicted.

Description

technical field [0001] The invention relates to an industrial process soft-sensing modeling method, in particular to an industrial process soft-sensing method based on an integrated independent element regression model. Background technique [0002] In modern industrial processes, many important parameters that can reflect product quality or production status cannot be effectively measured online due to technical or economic constraints. Data-driven soft-sensing methods are created to solve such problems. The basic idea of ​​the soft-sensing method is to use some easy-to-measure process variables and other parameters to establish a prediction model that can estimate some parameters and variables that cannot be directly measured or are difficult to measure online, so as to achieve indirect measurement of these variables or parameters. In recent years, due to the advantages of strong versatility, convenient implementation, and simple maintenance, soft sensing methods have rec...

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Application Information

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IPC IPC(8): G05B23/02
CPCG05B23/0218
Inventor 童楚东蓝艇
Owner NINGBO UNIV
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