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

A Distributed Process Monitoring Method Based on Multi-Block Independent Component Analysis Algorithm

A technology of independent component analysis and process monitoring, applied in the direction of program control, electrical program control, comprehensive factory control, etc., can solve the problem of not considering the integrity of the production system

Active Publication Date: 2022-03-18
恩施自治州聪慧科技发展有限责任公司
View PDF10 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, if each production unit is modeled and monitored independently, the integrity of the entire production system has not been considered

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 Distributed Process Monitoring Method Based on Multi-Block Independent Component Analysis Algorithm
  • A Distributed Process Monitoring Method Based on Multi-Block Independent Component Analysis Algorithm
  • A Distributed Process Monitoring Method Based on Multi-Block Independent Component Analysis Algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The method of the present invention will be described in detail below in conjunction with the accompanying drawings and specific examples of implementation.

[0040] The invention discloses a distributed process monitoring method based on a multi-block independent component analysis algorithm. The specific implementation process of the method of the invention and its superiority over the existing methods will be described below in conjunction with a specific industrial process example.

[0041] 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 TE process object can simulate a variety of different fault t...

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 distributed process monitoring method based on a multi-block independent component analysis algorithm, and aims to propose a novel multi-block independent component analysis algorithm, and use the algorithm to implement distributed non-Gaussian process monitoring, so that it can be used in construction In the process of modeling, the uniqueness of each sub-block and the integrity between sub-blocks are considered at the same time. In the process of implementing multi-block modeling, the method of the present invention does not simply extract score vectors for each sub-block, but an interleaved one-by-one extraction strategy from the whole to local sub-blocks, and then from local sub-blocks to the whole. Therefore, the novel multi-block independent component analysis algorithm proposed by the method of the present invention not only considers the uniqueness of each sub-block, but also considers the overall integrity. Therefore, the method of the present invention is a brand-new distributed non-Gaussian process monitoring method. In addition, the superiority of the method of the present invention will be verified in specific implementation cases, thus illustrating that the method of the present invention is a more preferred non-Gaussian process monitoring method.

Description

technical field [0001] The invention relates to a data-driven process monitoring method, in particular to a distributed process monitoring method based on a multi-block independent component analysis algorithm. Background technique [0002] Under the upsurge of industrial "big data", modern industrial processes are gradually moving towards digital management. Since production process objects can store and measure massive amounts of data offline and online, these data contain potential information that can reflect the operating status of the production process, and the use of sampled data to monitor the operating status of the process has been favored by many scholars. In fact, both academia and industry have invested a lot of manpower and material resources in the research of process monitoring methods with fault detection as the core task. In the field of data-driven process monitoring research, statistical process monitoring is the most studied method, among which princip...

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
CPCG05B19/4185G05B2219/31088Y02P90/02
Inventor 唐俊苗童楚东朱莹
Owner 恩施自治州聪慧科技发展有限责任公司
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