Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Soft sensing method for butane content in a dealanizer based on stacking

A technology of butane and soft measurement of a butane tower, applied in the field of industrial process prediction and soft measurement, can solve problems such as the inability to make good use of the Stacking model, and achieve the effect of improving the accuracy of real-time prediction

Active Publication Date: 2022-07-05
ZHEJIANG UNIV
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In fact, the first layer learner in the Stacking model reported in this patent has only one random weight neural network, and the second layer learner uses the same model as the first layer learner, which cannot make good use of the advantages of the Stacking model

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Soft sensing method for butane content in a dealanizer based on stacking
  • Soft sensing method for butane content in a dealanizer based on stacking
  • Soft sensing method for butane content in a dealanizer based on stacking

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0045]The present invention is described below in conjunction with a concrete butane content prediction embodiment of the butane tower:

[0046] The first 1596 samples are used as the training set to train the integrated learning soft sensor model, and the last 798 samples are used as the test set to verify the performance of the integrated learning soft sensor model. effectiveness. In this process, seven process variables are selected to model the butane content at the bottom of the debutanizer, these seven process variables are the top temperature, top pressure, reflux, flow to the next stage, sixth Block plate temperature, column bottom temperature 1, column bottom temperature 2, such as figure 1 shown in.

[0047] Next, the implementation steps of the present invention will be described in detail in combination with the specific process, such as image 3 shown, specifically:

[0048] 1. Use 1596 training samples to train an XGBOOST regression model, and obtain the impo...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a stacking-based soft measurement method for butane content in a dealanizer. The method expands the process variables at the current sampling time through a time sliding window, uses historical process data to solve the process dynamics problem, and enhances the first-layer learner in the ensemble learning model by introducing a feature perturbation mechanism and using a non-homogeneous learner. Then, the output of the first-layer learner is combined with the stacking integration strategy and the second-layer learner to obtain the final predicted value of the butane content. The present invention effectively improves the real-time prediction of the butane content of the butane tower precision.

Description

technical field [0001] The invention belongs to the field of industrial process prediction and soft measurement, in particular to a stacking-based soft measurement method for butane content in a debutanizer. Background technique [0002] In actual industrial processes, there are many variables that are difficult to measure directly or that are expensive to measure, and these variables often greatly affect product quality. Industrial process soft sensing technology is a method of estimating the true value of the variable to be measured by establishing a mathematical model between the variable to be measured and other easily measurable variables. Soft measurement technology is mainly divided into two categories: mechanism modeling and data-based modeling. The development of computer technology and machine learning has made the application of data-based modeling soft-sensor methods more and more widely. Common soft measurement methods based on data modeling include support vec...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/28G06F30/27G06K9/62G06N7/00G06N20/10G06F113/08G06F119/14
CPCG06F30/28G06F30/27G06N20/10G06F2113/08G06F2119/14G06N7/01G06F18/214Y02P90/30
Inventor 葛志强庄新镇孔祥印
Owner ZHEJIANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com