Machine learning oriented equipment component health management method and system

A machine learning and health management technology, applied in the direction of instruments, data processing applications, resources, etc., can solve problems such as being unable to develop PHM systems by itself

Inactive Publication Date: 2018-12-07
FOSHAN UNIVERSITY
View PDF6 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] Domestic companies have owned massive amounts of data for decades, but they are unable to develop PHM systems by themselves

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
  • Machine learning oriented equipment component health management method and system
  • Machine learning oriented equipment component health management method and system
  • Machine learning oriented equipment component health management method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0052] refer to Figure 1~5 , a machine learning-oriented equipment component health management method and system provided by the present invention, the method includes the following steps:

[0053] A. Establish a status trend analysis system for equipment components;

[0054] B. Establish a health assessment system for equipment components;

[0055] C. Establish a decision-making optimization system for equipment components, and make suggestions for equipment in poor health or a certain component system according to the multidimensional variables of equipment components.

[0056] Further, the step A specifically includes:

[0057] Carry out the status trend analysis of equipment components, extract the status trend change characteristics of components by independently associating the relevant multi-dimensional variables of the components, and combine the knowledge system obtained by the normal and abnormal state machine learning technology to establish a status trend analys...

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 relates to the technical field of equipment component health management, in particular to a machine learning oriented equipment component health management method and a machine learningoriented equipment component health management system. According to the method and the system provided by the invention, the component state health degree is determined through establishing a state trend analysis system, a health evaluation system of the equipment components is established for evaluating health of the integral equipment or one component thereof shown in the evaluation state, further a decision-making optimization system of the equipment components is established for evaluating health states of the equipment components effectively, and suggestions are made for the equipment orone component with poor health state systematically.

Description

technical field [0001] The invention relates to the technical field of equipment component health management, in particular to a machine learning-oriented equipment component health management method and system. Background technique [0002] Refers to failure prediction and health management (PHM), which is proposed to meet the requirements of self-guarantee and self-diagnosis, and is an upgraded development of condition-based maintenance (CBM). It emphasizes status awareness in asset and equipment management, monitors equipment health status, frequent fault areas and cycles, and predicts the occurrence of faults through data monitoring and analysis, thereby greatly improving operation and maintenance efficiency. In order to achieve PHM, in addition to the guarantee of physical basic conditions, it requires not only big data analysis technology, but also very intensive industry knowledge, experience and models as support. [0003] Diagnosis is the process of monitoring the ...

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): G06Q10/06G06Q10/00
CPCG06Q10/06393G06Q10/20
Inventor 张彩霞王向东胡绍林王新东
Owner FOSHAN UNIVERSITY
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