Numerical control machine tool fault monitoring and diagnosis system based on data mining

A technology of data mining and fault monitoring, applied in the fields of electrical digital data processing, digital data information retrieval, special data processing applications, etc., to achieve the effect of fast and accurate diagnosis results, simple data acquisition, and automation of the diagnosis process

Inactive Publication Date: 2021-03-12
BEIHANG UNIV
View PDF5 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention aims at the real-time, intelligent and autonomous fault monitoring and diagnosis requirements of high-end CNC machine tools for precision machining, and is designed to solve the problems of real-time, intelligent and autonomous fault monitoring and diagnosis of CNC machine tools

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
  • Numerical control machine tool fault monitoring and diagnosis system based on data mining
  • Numerical control machine tool fault monitoring and diagnosis system based on data mining
  • Numerical control machine tool fault monitoring and diagnosis system based on data mining

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0040] see figure 1 , the present invention is a numerically controlled machine tool fault monitoring and diagnosis system based on data mining, comprising a numerically controlled machine tool equipment data management module, a data interpretation module, an intelligent fault diagnosis module, a data mining module and a human-computer interaction module. The equipment data management module consists of a database, including equipment operation me...

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 numerical control machine tool fault monitoring and diagnosis system based on data mining. The system comprises a data management module, a data interpretation module, an intelligent fault diagnosis module, a data mining module and a man-machine interaction module. The data management module supports real-time importing of current data and batch importing and exporting ofhistorical data; the data interpretation module performs preprocessing, feature extraction and symptom extraction on the data; the intelligent fault diagnosis module is used for reasoning system-level faults by synthesizing the obtained symptoms and diagnosis knowledge; the data mining module autonomously mines an unknown fault mode alarm criterion and a diagnosis knowledge rule, and updates an alarm criterion library and a diagnosis knowledge base; the man-machine interaction module realizes setting control of fault monitoring and diagnosis processes and real-time display of results; the system has the advantages that machine tool operation is fully utilized to naturally generate data, deep modeling of a machine tool with a complex mechanism is not needed, the knowledge bottleneck of a traditional expert system type diagnosis system is broken through, the diagnosis process is automatic, and diagnosis is rapid and accurate.

Description

technical field [0001] The invention relates to the field of fault diagnosis of numerical control machine tools, in particular to a data mining-based fault monitoring and diagnosis system of numerical control machine tools. Background technique [0002] The higher and higher requirements for high-end military products on the quality of workmanship, as well as the higher and higher requirements for mass production capabilities of high-intensity operations and difficult model tasks, highlight the urgent need to strengthen the development and application of equipment. Machine tools are known as the "mother of industry" and represent the strength of a country's manufacturing capabilities. At present, my country's domestic high-end CNC machine tools can replace imports to solve the problem, but there is still a gap with foreign technologies in terms of key technologies such as machine tool reliability and precision maintenance. [0003] Fault diagnosis technology of CNC machine ...

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): G06F16/2458G06N5/02B23Q17/00G06N5/04
CPCG06F16/2465G06N5/04G06N5/022B23Q17/00
Inventor 金阳崔朗福白成刚申振丰张庆振韩晓萱宋莉君周理风朱力敏冯强左宇杰穆晨亮
Owner BEIHANG UNIV
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