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Numerical control machine tool cutter remaining service life prediction method and system and application

A CNC machine tool and life prediction technology, applied in the field of machinery, can solve problems such as poor generalization ability of prediction models, achieve the effect of improving generalization ability, customer service limitations, and improving model prediction accuracy

Active Publication Date: 2021-10-29
XIDIAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] Aiming at the problems existing in the prior art, the present invention provides a method, system and application for predicting the remaining service life of a CNC machine tool tool, in particular to a method, system and application for predicting the remaining service life of a CNC machine tool tool based on multi-source information fusion, It aims to solve the problem of poor generalization ability of predictive models built with a single signal in the prior art

Method used

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  • Numerical control machine tool cutter remaining service life prediction method and system and application
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  • Numerical control machine tool cutter remaining service life prediction method and system and application

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Embodiment 1

[0079] refer to figure 2 , the steps for realizing the present invention will be further described in detail.

[0080] Step 1, signal acquisition and processing.

[0081] The first step is to collect the signals during the working process of the CNC machine tool, that is, the controller signal and the sensor signal. The controller signal mainly includes the spindle load and the mechanical coordinates in three directions, namely the x-axis mechanical coordinates, y-axis mechanical coordinates and z-axis mechanical coordinates , the sensor signal mainly includes the current signal and the vibration signal in three directions, that is, the vibration signal in the x-axis direction, the vibration signal in the y-axis direction, the vibration signal in the z-axis direction and the current signal.

[0082] The second step is to preprocess the collected signals. First, the signals collected when not in contact with the processing object are eliminated according to the mechanical coo...

Embodiment 2

[0105] The data set used in the embodiment of the present invention is the Foxconn machining tool data in the second industrial big data innovation competition. The data is collected from the real machining process of the CNC machine tool. A brand new tool is normally processed from the beginning to the end of the tool life. Stop collecting.

[0106] 1) Signal acquisition and processing.

[0107]1.1) Collect the signals during the working process of the CNC machine tool, that is, the controller signal and the sensor signal. The controller signal mainly includes the spindle load and the mechanical coordinates in three directions, namely the x-axis mechanical coordinate, the y-axis mechanical coordinate and the z-axis mechanical coordinate. The sensor The signals mainly include current signals and vibration signals in three directions, namely, vibration signals in the x-axis direction, vibration signals in the y-axis direction, vibration signals in the z-axis direction, and curr...

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Abstract

The invention belongs to the technical field of machinery, and discloses a numerical control machine tool cutter remaining service life prediction method and system and application. The numerical control machine tool cutter remaining service life prediction method comprises the steps of collecting controller signals and sensor signals in the working process of a numerical control machine tool, and carrying out the preprocessing, feature extraction and feature selection of the signals; excavating information related to cutter wear in various signals; and establishing a cutter remaining service life prediction model by using a long-short term memory network and an attention mechanism to realize the remaining service life prediction of the numerical control machine tool cutter. The controller signal and the sensor signal in the working process of the numerical control machine tool are collected, the cutter remaining service life prediction model is established through multi-source information, the cutter abrasion condition reflected by different types of signals is fully considered, the limitation of establishing the prediction model through a single signal in the prior art is effectively overcome, and therefore, the generalization ability of the cutter remaining service life prediction model is improved.

Description

technical field [0001] The invention belongs to the technical field of machinery, and in particular relates to a method, system and application for predicting the remaining service life of a CNC machine tool tool. Background technique [0002] At present, as a very important part in CNC machining, the problem caused by tool wear is one of the main problems in the process of CNC machining. In the milling process of CNC machine tools, the wear and degradation of cutting tools is inevitable. Once the tool fails, the surface quality of the workpiece will not meet the requirements, resulting in low processing efficiency, and even damage to the machine tool when the wear is severe. Therefore, it is of great significance to effectively predict the remaining service life of the tool to improve the production efficiency of CNC machine tools. At present, data-driven combined with machine learning is the mainstream method and technology in the field of tool life prediction technology...

Claims

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Application Information

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IPC IPC(8): B23Q17/00B23Q17/09
CPCB23Q17/00B23Q17/008B23Q17/09B23Q17/0995Y02P90/30
Inventor 刘尧叶礼伦陈改革孔宪光
Owner XIDIAN UNIV
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