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

A Dynamic Process Monitoring Method Based on Dynamic Orthogonal Component Analysis

A dynamic process and component analysis technology, applied in the direction of program control, electrical program control, comprehensive factory control, etc., can solve problems such as sequence correlation considerations

Active Publication Date: 2021-03-09
SHENZHEN LOTUT INNOVATION DESIGN CO LTD
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It can be seen that the classic PCA algorithm fails to take the serial correlation of samples into account

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
  • A Dynamic Process Monitoring Method Based on Dynamic Orthogonal Component Analysis
  • A Dynamic Process Monitoring Method Based on Dynamic Orthogonal Component Analysis
  • A Dynamic Process Monitoring Method Based on Dynamic Orthogonal Component Analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] The method of the present invention will be described in detail below in conjunction with the accompanying drawings and specific examples of implementation.

[0034] Such as figure 1 As shown, the present invention discloses a dynamic process monitoring method based on dynamic orthogonal component analysis. The specific implementation process of the method of the present invention and its advantages over the existing methods will be described below in conjunction with an example of a specific industrial process.

[0035] The application object is from Tennessee-Eastman (TE) chemical process experiment, and the prototype is an actual process flow of Eastman chemical production workshop. Currently, the TE process has been widely used in fault detection research as a standard experimental platform due to its complexity. The whole TE process includes 22 measured variables, 12 manipulated variables, and 19 component measured variables. The collected data are divided into 22...

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 dynamic process monitoring method based on dynamic orthogonal component analysis. On the basis of the traditional principal component analysis algorithm, the method of the invention further considers how to further consider the relationship between the latent feature components and the time-delay measurement data. Orthogonal properties. For this reason, the method of the invention deduces a dynamic orthogonal component analysis algorithm first, and then implements dynamic process monitoring on the basis of the algorithm. Compared with the traditional dynamic process monitoring method, the method of the present invention achieves an effect superior to the traditional PCA or dynamic PCA method in the monitoring effect of the dynamic process. In addition, the two stages of off-line modeling and on-line monitoring of the method of the present invention will not increase the amount of extra calculation. It can be said that the method of the present invention is a more preferred dynamic process monitoring method.

Description

technical field [0001] The invention relates to a data-driven fault detection method, in particular to a dynamic process monitoring method based on dynamic orthogonal component analysis. Background technique [0002] The purpose of process monitoring is to find faults timely and accurately, which is of great significance to ensure safe production and maintain stable product quality. At present, due to the large-scale construction of modern chemical processes and the wide application of advanced instrumentation and computer technology, massive data can be collected in the production process, and the mainstream implementation technical means of process monitoring has gradually changed from a method based on a mechanism model to a data-driven method. The development mode that the sampling data is easy to obtain but the mechanism model is difficult to obtain makes the traditional fault detection method based on the mechanism model gradually decline. In contrast, the data-driven...

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): G05B19/418
CPCG05B19/41885G05B2219/32339Y02P90/02
Inventor 皇甫皓宁童楚东朱莹
Owner SHENZHEN LOTUT INNOVATION DESIGN CO LTD
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