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

Industrial process data-based method of alarm limit self-learning system based on

A technology for learning systems and industrial processes, applied in data processing applications, predictions, calculations, etc., to achieve the effect of improving stability and reducing time load

Inactive Publication Date: 2014-07-09
AUTOMATION RES & DESIGN INST OF METALLURGICAL IND
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] The purpose of the present invention is to provide a method of an alarm limit self-learning system based on industrial process data, which solves the limitation of manually setting the alarm limit and realizes the method of online calculation of the alarm limit

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
  • Industrial process data-based method of alarm limit self-learning system based on
  • Industrial process data-based method of alarm limit self-learning system based on

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055] Provide the concrete implementation method of the present invention below. The input data for alarm limit calculation generally comes from real-time data on the industrial site, data once every 5 seconds or once every 10 seconds is enough, and data with too high frequency is not required. Under normal circumstances, the calculation of the small period is performed once an hour, and the calculation of the large period is performed once a month.

[0056] In the initialization phase, the values ​​of the following calculation parameters need to be initialized:

[0057] Data sampling frequency: default 5-10 seconds

[0058] Number of data partitions: 20 by default

[0059] Number of extended partitions: default 3 (extend three intervals at the top and bottom)

[0060] Upper and lower overrun alarm interval data threshold: default 0.25%

[0061] Upper and lower limit alarm interval data threshold: default 5%

[0062] Normal data interval (from low limit to high limit) da...

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 an industrial process data-based method of an alarm limit self-learning system, belonging to the technical field of automatism of industrial manufacturing. The industrial process data-based method comprises the following steps of: firstly, dividing date into different intervals according to different algorithmic rules; secondly, computing a data accumulating amount according to a certain cycle and a frequency value for the data in each interval; thirdly, continuously processing according to the cycle till the end of a major cycle, and computing to obtain an accumulating value of the whole major cycle and the data distribution condition of each interval; and fourthly, computing alarm limit information by using an algorithm according to the accumulating data and the frequency data. The industrial process data-based method of the alarm limit self-learning system has the advantage that the limitation that the alarm limit is set manually is overcome and a method for computing the alarm limit on line can be realized.

Description

technical field [0001] The invention belongs to the technical field of industrial manufacturing automation, and in particular provides a method for an alarm limit self-learning system based on industrial process data, so as to intelligently correct the alarm limit in order to predict the production state more accurately in the production field. Purpose. Background technique [0002] In the current industrial manufacturing industry, the production process is very complicated, and various sudden production failures and errors are inevitable in the production process. In order to effectively capture and display this information, most of them have introduced computer monitoring systems. In the monitoring system Generally, a built-in alarm module is used to capture abnormal production information, provide warnings for production schedulers, and allow them to take timely measures to make reasonable adjustments to process equipment and production rhythms to avoid losses caused by p...

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): G06Q10/04
Inventor 李勇徐化岩孙彦广于立业
Owner AUTOMATION RES & DESIGN INST OF METALLURGICAL IND
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