Check patentability & draft patents in minutes with Patsnap Eureka AI!

Mechanical fault predictive maintenance method and system based on knowledge graph

A knowledge map and mechanical failure technology, applied in the field of predictive maintenance of industrial clusters, can solve problems such as poor interpretability and large amounts of data, and achieve the effects of reducing equipment failure rates, high feasibility, and improving economic benefits

Pending Publication Date: 2022-01-04
SHANDONG NORMAL UNIV
View PDF2 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] In order to solve the disadvantages of poor interpretability and the need for a large amount of data in the existing technology, the present invention provides a mechanical failure predictive maintenance method and system based on knowledge graph

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
  • Mechanical fault predictive maintenance method and system based on knowledge graph
  • Mechanical fault predictive maintenance method and system based on knowledge graph
  • Mechanical fault predictive maintenance method and system based on knowledge graph

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] This embodiment provides a mechanical fault predictive maintenance method based on knowledge graph;

[0051] Such as figure 1 As shown, the predictive maintenance method for mechanical failure based on knowledge graph includes:

[0052] S101: Obtain the name of the mechanical equipment components to be maintained and the information of the mechanical equipment to be maintained; for the mechanical equipment to be maintained, initially build a knowledge graph of mechanical failure from top to bottom;

[0053] S102: Supplement and improve the preliminary construction of the mechanical fault knowledge map in a bottom-up manner;

[0054] S103: Select the corresponding data set for the mechanical equipment to be maintained; assign multiple features to each state of each component in the data set according to the supplemented mechanical fault knowledge map; wherein, each feature corresponds to a feature value;

[0055] S104: Define fuzzy variables, membership functions and f...

Embodiment 2

[0195] This embodiment provides a mechanical failure predictive maintenance system based on knowledge graph;

[0196] Mechanical failure predictive maintenance system based on knowledge graph, including:

[0197] The obtaining module is configured to: obtain the name of the mechanical equipment part to be maintained and the information of the mechanical equipment to be maintained; construct a mechanical fault knowledge map from top to bottom for the mechanical equipment to be maintained;

[0198] The supplementary module is configured to: supplement and improve the initially constructed mechanical fault knowledge map in a bottom-up manner;

[0199] The feature assignment module is configured to: select the corresponding data set for the mechanical equipment to be maintained; assign multiple features to each state of each component in the data set according to the supplementary mechanical fault knowledge map; wherein, each A feature corresponds to an eigenvalue;

[0200] A ru...

Embodiment 3

[0206] This embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein, the processor is connected to the memory, and the one or more computer programs are programmed Stored in the memory, when the electronic device is running, the processor executes one or more computer programs stored in the memory, so that the electronic device executes the method described in Embodiment 1 above.

[0207] It should be understood that in this embodiment, the processor can be a central processing unit CPU, and the processor can also be other general-purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic devices , discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, o...

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 mechanical fault predictive maintenance method and system based on a knowledge graph. The method comprises the following steps: acquiring a name of a to-be-maintained mechanical equipment part and information of to-be-maintained mechanical equipment; preliminarily constructing a mechanical fault knowledge graph for the to-be-maintained mechanical equipment from top to bottom; supplementing and perfecting the preliminarily constructed mechanical fault knowledge graph from bottom to top; selecting a corresponding data set for the to-be-maintained mechanical equipment; according to the supplemented and perfected mechanical fault knowledge graph, endowing each state of each component in the data set with a plurality of features; defining a fuzzy variable, a membership function and a fuzzy rule according to the features and the feature values; and taking the value of the fuzzy variable as an input parameter, performing fuzzification processing on the input parameter by adopting a membership function, performing fuzzy reasoning on the fuzzified data by adopting a fuzzy rule, and performing defuzzification processing on the data obtained by fuzzy reasoning to obtain a fault degree priority. Predictive maintenance of mechanical faults is realized.

Description

technical field [0001] The invention relates to the technical field of predictive maintenance of industrial clusters, in particular to a method and system for predictive maintenance of mechanical failures based on knowledge graphs. Background technique [0002] The statements in this section merely mention the background technology related to the present invention and do not necessarily constitute the prior art. [0003] Predictive maintenance is scheduled and implemented based on the operating status of the equipment and system itself. It is called CBM (Condition Based Maintenance) condition-based maintenance. This maintenance method has some obvious advantages. Because the intervention of maintenance work is completely based on the current state of the equipment and system itself, it avoids unnecessary downtime caused by redundant intervention and prevents Losses caused by cascading failures. In a modern industrial production environment, especially in assembly line tas...

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): G06Q10/00G06Q10/04G06F16/36G06N5/02G06N5/04G06N20/00
CPCG06Q10/20G06Q10/04G06N5/048G06N5/02G06F16/367G06N20/00
Inventor 闫伟石玉王晨张亮王吉华
Owner SHANDONG NORMAL UNIV
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com