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

Probabilistic principal component regression model-based method for soft sensing of butane content of debutanizer

A technology of butane and principal element regression in a butane tower is applied in the field of soft sensing modeling and on-line detection of butane content in a butane tower, which can solve the problem of not well considering process data noise information, model failure performance, degradation And other issues

Inactive Publication Date: 2013-11-13
ZHEJIANG UNIV
View PDF3 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Principal component regression analysis is a widely used soft sensor modeling method. However, because the noise information of the process data is not well considered in the modeling process, the model fails or fails in some actual soft sensor processes. Performance drop

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
  • Probabilistic principal component regression model-based method for soft sensing of butane content of debutanizer
  • Probabilistic principal component regression model-based method for soft sensing of butane content of debutanizer
  • Probabilistic principal component regression model-based method for soft sensing of butane content of debutanizer

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0014] Aiming at the problem of detecting the butane content in the debutanizer, the invention uses variables that are easy to measure in the process and uses a probability principal component regression analysis model to perform on-line soft measurement of the butane content in the process.

[0015] The main steps of the technical solution adopted in the present invention are respectively as follows:

[0016] Step 1: Collect the data of each process variable in debutanizer through distributed control system and real-time database system: X={x i ∈R m} i=1,2,…,n . Among them, n is the number of samples, and m is the number of process variables. Store these data in the historical database respectively, and select some data as samples for modeling;

[0017] 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, and use it as the output y∈R of the soft sensor m...

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 soft sensing method based on a probabilistic principal component regression model for online detection of butane content of a debutanizer. Principal component regression model is a common modeling approach for soft sensing. However, as noise information of process data is not taken into consideration well, the principal component regression model fails in many real processes. The method introduces a probabilistic modeling approach which converts the conventional principal component regression model into a probabilistic form, which is a soft-sensing model based on probabilistic principal component regression. Compared to the conventional principal component regression model, the probabilistic principal component regression model allows modeling on the process data and the noise information at the same time and provides more complete data information, so that the soft sensing results are more reliable.

Description

technical field [0001] The invention belongs to the field of soft sensor modeling and application in the chemical production process, and in particular relates to a soft sensor modeling and online detection method for butane content in a debutanizer based on a probability principal component regression model. Background technique [0002] In the debutanizer, how to get the butane content online is very important for the control of the debutanizer, which directly affects the operation performance of the whole process and the quality index of the product. However, for the measurement of butane content, there is currently a lack of direct measurement methods, and indirect soft measurement methods are often needed. That is, other easily measurable variables in the process are used to estimate the butane content in real time. Principal component regression analysis is a widely used soft sensor modeling method. However, because the noise information of the process data is not wel...

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 Applications(China)
IPC IPC(8): G01N33/00
Inventor 葛志强宋执环
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