Intelligent monitoring management method and system for rectification production process

Through intelligent sensors collecting and preprocessing distillation production data, building a support vector regression SVR model to predict material quality, and displaying and storing data through a visual interface, the problem of lack of flexibility and slow response speed in the state classification model in the existing technology is solved, and efficient monitoring and intelligent management of distillation production process is achieved.

CN119719927APending Publication Date: 2025-03-28XINJIANG UNIVERSITY
0 Cites 1 Cited by

Patent Information

Application Number
CN202411792382.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-07
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

The existing state classification model lacks flexibility in the distillation production process and is difficult to adapt to the dynamically changing production environment, resulting in slow response speed and timely early warnings, resulting in potential economic losses and safety hazards.

Method used

By deploying intelligent sensors to collect production data and preprocess it, feature vectors are extracted; support vector regression SVR model is built to predict material quality, and the model is adjusted through feedback data; visual interface is built to display material quality, and the collected and analyzed production data are stored.

Benefits of technology

It improves the monitoring efficiency and intelligence level of the distillation process, improves production safety and economy, and reduces the probability of abnormal situations.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses an intelligent monitoring management method and system for a rectification production process, and relates to the technical field of intelligent management, and the method comprises the steps: deploying an intelligent sensor, collecting production data, carrying out the preprocessing, and extracting a feature vector of the preprocessed production data; constructing a support vector regression SVR model to predict material quality, and collecting feedback data to adjust the support vector regression SVR model; and constructing a visual interface to display the material quality, and storing, collecting and analyzing the generated production data. The method comprises the following steps: deploying an intelligent sensor to collect production data and pre-process the production data, and extracting feature vectors of the pre-processed production data; constructing a support vector regression SVR model to predict material quality, and collecting feedback data to adjust the support vector regression SVR model; the monitoring efficiency and the intelligent level of the rectification process are improved, the production safety and economy are improved, and the probability of occurrence of abnormal conditions is reduced.
Need to check novelty before this filing date? Find Prior Art