A quality-related process monitoring method based on weighted partial mutual information

A quality-related, process monitoring technology, applied in program control, electrical program control, comprehensive factory control, etc., can solve the problems of loss of trust in the monitoring system, affecting product quality, affecting normal working conditions, etc., to reduce interference and alarm, improve The detection rate and the effect of improving efficiency

Active Publication Date: 2021-06-18
SHANDONG UNIV OF SCI & TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Quality-related failures that occur in actual industrial processes can seriously affect product quality
At the same time, the frequent occurrence of interference alarms that have nothing to do with quality will make users lose trust in the monitoring system and affect normal working conditions.

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 quality-related process monitoring method based on weighted partial mutual information
  • A quality-related process monitoring method based on weighted partial mutual information
  • A quality-related process monitoring method based on weighted partial mutual information

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0056] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0057] A quality-related process monitoring method based on weighted partial mutual information, the process is as follows figure 2 shown, including the following steps:

[0058] Step 1: variable selection; specifically include the following steps:

[0059] Step 1.1: Assuming that the detected object contains m process variables and d quality variables, perform n times of sampling to obtain the historical data set under normal working conditions and

[0060] Standardize the original process data X and quality data Y respectively, as shown in formulas (1) and (2):

[0061]

[0062]

[0063] Among them, μ x and the diagonal matrix Σ x Represent the mean and standard deviation of X, respectively, μ y and the diagonal matrix Σ y Represent the mean and standard deviation of Y, respectively;

[0064] Step 1.2: According to formula (3...

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 quality-related process monitoring method based on weighted partial mutual information, which belongs to the field of fault diagnosis. The present invention combines partial mutual information and Bayesian weighted fusion, under the supervision of multiple quality indicators, selects process variables that are closely related to quality, models the selected variables through correlation meta-analysis, and obtains a process variable that contains the main information of quality changes. related element. The process data space is divided into two subspaces, and statistics are constructed in the subspaces for fault detection. This method can improve the detection rate of quality-related faults, significantly reduce false alarms, and improve the efficiency of actual industrial processes; this paper The inventive method can effectively extract meaningful information hidden in process variables and quality variables; by constructing statistical indicators in two orthogonal subspaces respectively, faults related to quality can be detected, and interference alarms not related to quality can be reduced at the same time.

Description

technical field [0001] The invention belongs to the field of fault diagnosis, and in particular relates to a quality-related process monitoring method based on weighted partial mutual information. Background technique [0002] Product quality is closely related to production efficiency in actual industrial processes. Quality-related failures that occur in real industrial processes can seriously affect product quality. At the same time, the frequent occurrence of interference alarms that have nothing to do with quality will cause users to lose trust in the monitoring system and affect normal working conditions. Contents of the invention [0003] Aiming at the above-mentioned technical problems in the prior art, the present invention proposes a quality-related process monitoring method based on weighted partial mutual information, which is reasonably designed, overcomes the shortcomings of the prior art, and has good effects. [0004] In order to achieve the above object, ...

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
CPCG05B19/41875G05B2219/32368Y02P90/02
Inventor 周东华王彦文陈茂银王敏纪洪泉
Owner SHANDONG UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap