Tobacco shredded process parameter self-healing control method and system

Abstract

The invention discloses a control method for parameters self-tuning of tobacco shred production process, comprising the steps of: collecting process parameters of all the processes in the tobacco shred production process; establishing a regression model by adopting process parameters, training the regression model, validating a target variable and an argument, selecting several arguments that havea significant influence on the target variable from the target variable and the argument, screening the independent variable according to a coefficient weight, obtaining an independent variable corresponding to the weight in a preset range, performing a cross validation, taking the process parameters into the targeted regression model, and obtaining a targeted regression model of the corresponding class; when an exception occurs in the process parameters in any category, removing the exception occurred in process parameters of the current process and the output parameters in the next processthrough the targeted regression model corresponding to abnormal process parameters, thereby realizing the control process of the parameters self-tuning. According to the control method and the systemfor the parameters self-tuning of the tobacco shred production process, multi-parameter correlation model of each monitoring control parameter is obtained, and the invention can be used for global parameter optimization of tobacco shred making process.

Description

technical field [0001] The invention relates to the technical field of industrial automation, in particular to a method and system for self-healing control of tobacco shred process parameters. Background technique [0002] In the cigarette processing process, the silk-making process is an important link. The quality of its process not only directly affects the work efficiency of the subsequent rolling process, but also is closely related to the quality of finished cigarettes. However, in the actual production process, abnormal parameter alarms will inevitably occur. Since the silk making process is a multi-parameter, multi-coupling, non-linear, and multi-interference continuous production process, when an abnormal parameter alarm occurs, it is very difficult for the operator. It is difficult to quickly and effectively trace and locate the cause of the upstream abnormality, which will lead to difficulty in eliminating the abnormal parameter adjustment and low efficiency; on t...

AI Technical Summary

Problems solved by technology

However, in the actual production process, abnormal parameter alarms will inevitably occur. Since the silk making process is a multi-parameter, multi-coupling, non-linear, and multi-interference continuous production process, when an abnormal parameter alarm occurs, it is very difficult for the operator. It is difficult to quickly and effectively trace and locate the cause of the upstream abnormality, which will lead to difficulty in eliminating the abnormal parameter adjustment and low efficiency; on the other hand, there is no reliable evaluation method for the impact of abnormal parameters on downstream process parameters, and operators cannot Take corresponding measures to compensate and control in time, which will have a very large impact on the subsequent process flow

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