Industrial process data modeling method for online self-adaptive fine-tuning deep learning

Abstract

The invention provides an industrial process data modeling method for online self-adaptive fine-tuning deep learning. The method comprises the following steps: 1, acquiring process variables related to quality in an industrial process according to a sampling time sequence, labeling the process variables by utilizing the quality variables, constructing a labeled sample set, preprocessing data according to data characteristics, and dividing the labeled sample set into a training sample set and a query sample set; 2, training L restricted Boltzmann machines offline layer by layer in an unsupervised pre-training mode by using the training sample set, and stacking the L pre-trained restricted Boltzmann machines in sequence to form a stacked network. According to the industrial process data modeling method for online adaptive fine-tuning deep learning, the samples are selected based on similarity measurement to perform online updating on the offline model, the exclusive online model is established for the query samples, the accurate quality prediction of the query samples is completed, and the performance and precision of online prediction are improved.

Description

technical field [0001] The invention relates to the technical field of industrial processes, in particular to an industrial process data modeling method for online self-adaptive fine-tuning deep learning. Background technique [0002] With the implementation of the "Made in China 2025" national strategy, my country's industrial production level has been greatly improved and developed. Whether it is traditional industries such as chemical industry, papermaking, electric power and medicine, or modern industries such as robotics and 3D printing, there are increasingly higher requirements for the monitoring, control and optimization of the production process. In order to ensure the normal operation of industrial production processes, optimize the utilization efficiency of resources and effectively alleviate the pressure of environmental pollution, various advanced monitoring, control and optimization technologies have been widely used. The development and implementation of thes...

AI Technical Summary

Problems solved by technology

[0006] The present invention provides an industrial process data modeling method for online self-adaptive fine-tuning and deep learning. The problem of model prediction performance degradation caused by fluctuations, ingredient adjustments, and equipment aging

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