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Numerical control equipment remote diagnosis system based on neural network

A neural network and remote diagnosis technology, which is applied in the field of remote diagnosis system of numerical control equipment, can solve the problems of low maintenance efficiency and long detection time of numerical control machine tools, and achieve the effect of fast processing efficiency, improved detection efficiency and success rate, and fast processing speed.

Active Publication Date: 2020-04-14
NINGBO DAHONGYING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The main purpose of the present invention is to provide a remote diagnosis system for CNC equipment based on neural network, which solves the problems of long detection time and low maintenance efficiency of CNC machine tools

Method used

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  • Numerical control equipment remote diagnosis system based on neural network
  • Numerical control equipment remote diagnosis system based on neural network
  • Numerical control equipment remote diagnosis system based on neural network

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Experimental program
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Embodiment

[0037] A neural network-based remote diagnosis system for CNC equipment, basically as figure 1 As shown, including the server, the server includes the following modules:

[0038] Parameter collection module: used to obtain model parameters and operating parameters of CNC machine tools;

[0039] Preliminary diagnosis module: used for preliminary diagnosis of the CNC machine tool according to the operating parameters, analyzing whether the CNC machine tool is normal or faulty, and marking the operating parameters as faulty operating parameters when the CNC machine tool is initially diagnosed as faulty;

[0040] In-depth diagnosis module: used to import fault operating parameters into the established neural network fault diagnosis model for diagnosis, and output fault diagnosis results; the diagnosis results include fault types of CNC machine tools normal and CNC machine faults; neural network fault diagnosis model Construct based on BP neural network, collect data sample sets f...

Embodiment 2

[0051] The difference between the embodiment and the first embodiment is that the construction method of the shown neural network fault diagnosis model is as follows,

[0052] Step 1: Determine the input and output vectors:

[0053] According to the construction principle of the Boolean matrix, it is defined that in the fault diagnosis, there are m characteristic parameters, that is, the input characteristic vector P=(s 1 ,s 2 ,...,s m ), there are n fault types to be identified, that is, the output feature vector Q=(r 1 ,r 2 ,...,r n );

[0054] Step 2: Select the number of network layers: use a three-layer BP neural network, which are input layer, hidden layer, and output layer; according to the input feature vector and output feature vector described in step 1, determine the number of neurons in the input layer as a , where a=m, the number of neurons in the output layer is b, where b=n;

[0055] Step 3: Calculate the number of neurons in the hidden layer: the number ...

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Abstract

The invention relates to the technical field of numerical control equipment operation and maintenance, in particular to a numerical control equipment remote diagnosis system based on a neural network.The system comprises a server, and the server comprises a parameter acquisition module used for acquiring model parameters and operation parameters of a numerical control machine tool; a preliminarydiagnosis module for carrying out preliminary diagnosis on the numerical control machine tool according to the operating parameters, analyzing whether the numerical control machine tool is normal or faulty, and marking the operating parameters as faulty operating parameters when the numerical control machine tool is preliminarily diagnosed to be faulty; a deep diagnosis module for importing the fault operation parameters into an established neural network fault diagnosis model for diagnosis; a scheme screening module for searching a fault solution; and a fault information feedback module for remotely sending a fault type detection result and a solution to a machine tool field maintainer. The problems that the numerical control machine tool is long in detection time and low in maintenance efficiency are solved.

Description

technical field [0001] The invention relates to the technical field of operation and maintenance of numerical control devices, in particular to a remote diagnosis system for numerical control equipment based on a neural network. Background technique [0002] CNC machine tool is the abbreviation of numerical control machine tool, which is an automatic machine tool equipped with a program control system. It has the advantages of high flexibility, high processing precision, stable and reliable processing quality, and high productivity. The many advantages also lead to the increasingly complex structure of CNC machine tools and the higher degree of automation, which makes the fault diagnosis of CNC machine tools more difficult. Due to the existence of many uncertain factors in the manufacturing site, various failures will inevitably occur during the operation of CNC machine tools. [0003] Fault diagnosis and maintenance of CNC machine tools is a very important part of the pro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/406G06N3/04G06N3/08
CPCG05B19/406G06N3/084G06N3/045
Inventor 李华
Owner NINGBO DAHONGYING UNIV
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