Online equipment fault diagnosis platform of mobile terminal based on knowledge graph

A knowledge graph, equipment failure technology, applied in the computer field, can solve the problems of strong professionalism, few data sources, low practicability, etc., to achieve the effect of clear data structure, reasoning speed and accuracy improvement

Active Publication Date: 2020-02-07
HOHAI UNIV CHANGZHOU
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, the data sources of equipment fault diagnosis in the industry have the characteristics of few sources, strong professionalism, and low practicability. It is even more difficult to obtain sample data of machine tool faults and solutions.

Method used

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  • Online equipment fault diagnosis platform of mobile terminal based on knowledge graph
  • Online equipment fault diagnosis platform of mobile terminal based on knowledge graph
  • Online equipment fault diagnosis platform of mobile terminal based on knowledge graph

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Experimental program
Comparison scheme
Effect test

Embodiment approach

[0138] In the background management module shown in step S4, the present invention tries to further expand in the direction of data mining and in-depth analysis of the database. The implementation plan is as follows:

[0139] data mining

[0140] Enterprise:

[0141] The background includes all the monitoring of every search question asked by the user to obtain a higher probability CNC machine

[0142] The machine tool brand, type, and cause of the failure of the bed are sorted out in the background, and organized into a collection and fed back to each user.

[0143] User level:

[0144] 1) Description: Count all machine failure questions and input descriptions asked by a user

[0145] 2) Input data stream: Output data stream JSON: Database for structured data access: mongodb

[0146] 3) Processing logic: while (detecting that the user has sent the server the answer to a machine failure question and)

[0147] {Record the question-answer pair and store it in the database....

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Abstract

The invention discloses an online equipment fault diagnosis platform of a mobile terminal based on a knowledge graph. The method comprises the following steps: S1, establishing a numerical control machine tool information extraction module; S2, establishing a data cleaning and knowledge graph module; S3, establishing a question and answer extension module; and S4, establishing a background management module. Answers finally adopted by a user can be taken as new nodes to be brought into the relationship of the knowledge graph, and new records are added to a machine tool fault word segmentationdictionary and a problem template, so that a system is more intelligent in use, and the use experience of the user is improved.

Description

technical field [0001] The invention relates to a mobile terminal online device fault diagnosis platform based on a knowledge graph, belonging to the field of computer technology. Background technique [0002] With the deepening of industrial production automation, digitization, and intelligence, enterprises have higher and higher requirements for equipment reliability. Therefore, the research on the diagnosis and elimination of equipment faults has great practical significance. The Internet contains a large amount of valuable information, is an important data source for big data, and is also an important territory for experience exchange and retention. By collecting a large amount of scattered Internet data, obtaining related equipment faults and maintenance solutions on the Internet, and forming a knowledge map, the accuracy and application range of fault judgment can be improved. [0003] At present, the data sources for equipment fault diagnosis in the industry have th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/36G06F16/332G06F16/33G06F16/35G05B23/02G06F16/951
CPCG06F16/367G06F16/3329G06F16/3344G06F16/35G05B23/0245G06F16/951
Inventor 王钟贤姚潇谢尚旋刘旭宸李朝宇徐宁刘小峰
Owner HOHAI UNIV CHANGZHOU
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