Soft sensor modeling method for industrial non-stationary process based on local weighting factor model

A factor model and local weighting technology, applied in the direction of instruments, adaptive control, control/regulation systems, etc., can solve the problems that process dynamics and nonlinearity are not fully considered, achieve short prediction time, realize online estimation, The effect of accurate prediction results

Active Publication Date: 2022-04-08
CHINA JILIANG UNIV
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Problems solved by technology

Traditional probabilistic latent variable models, such as probabilistic principal component analysis, are mostly static linear methods, and process dynamics and nonlinearity have not been fully considered

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  • Soft sensor modeling method for industrial non-stationary process based on local weighting factor model
  • Soft sensor modeling method for industrial non-stationary process based on local weighting factor model
  • Soft sensor modeling method for industrial non-stationary process based on local weighting factor model

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Embodiment Construction

[0066] The present invention will be further described below in conjunction with drawings and embodiments.

[0067] The invention aims at the problem of detecting the butane content in the debutanizer, by using the variables that are easy to measure in the process, and using a local weighting factor analysis model, the online soft measurement is performed on the butane content in the process.

[0068] Embodiments of the present invention and its implementation process are as follows:

[0069] Step 1: Collect data of various process variables in debutanizer through distributed control system and real-time database system: training sample set X trian ∈R N×n , store these data in the historical database, and select some data as samples for modeling.

[0070] Step 2: Obtain the butane content value corresponding to the sample used for modeling in the historical database through on-site extraction and offline laboratory analysis as the output Y of the soft sensor model trian ∈R ...

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Abstract

The invention discloses an industrial non-stationary process soft sensor modeling method based on a local weighting factor model. The present invention introduces a sliding window, establishes a factor analysis model in each sliding window, inputs online query samples into each sliding window to obtain the local similarity between the query sample and the training sample and the local confidence of the query sample in the sliding window, and then The global weight of each training sample is obtained by synthesizing the results of all sliding windows, and the weighted average of the training sample set is calculated according to the global weight, and the query sample is predicted on the basis of the weighted average to obtain the predicted value of butane content of the query sample. The invention improves the accuracy of prediction results by establishing the weight relationship between online measurement samples and training samples.

Description

technical field [0001] The invention belongs to the field of industrial non-stationary process soft sensor modeling and application, in particular to an industrial non-stationary process soft sensor modeling and on-line detection method based on a local weighting factor model. Background technique [0002] Although the probabilistic model has been rapidly developed in the field of soft sensor modeling and has achieved fruitful results, most of the existing work is based on the assumption that the process is based on a stationary process. In practice, with changes in market demand, production planning Due to adjustments, external disturbances, etc., most industrial processes present non-stationary characteristics, that is, the statistical indicators of some process variables such as mean, variance, and covariance change with time. Industrial non-stationary processes widely exist in industrial production activities, and non-stationary The state of the process changes all the t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 何雨辰张丽芳方靖云王云宋执环严天宏
Owner CHINA JILIANG UNIV
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