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System and method for evaluating reliability of machine tool

A technology for evaluating systems and reliability, applied in biological neural network models, instruments, data processing applications, etc., can solve problems such as reducing the accuracy of processing objects and reducing the efficiency of processing processes, and achieve the effect of ensuring operational reliability.

Inactive Publication Date: 2018-11-20
WUHAN UNIV OF SCI & TECH
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Problems solved by technology

[0003] Tool wear is an inevitable form of failure in the machining process. The most direct harm it brings is to reduce the efficiency of the machining process on the one hand, and to reduce the accuracy of the machining object on the other hand.

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  • System and method for evaluating reliability of machine tool

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Embodiment Construction

[0022] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0023] A machine tool tool reliability evaluation system provided by the present invention includes a terminal information processing module, a data acquisition module, a vibration monitoring module, a micro-optical module, and an image processing module; and a terminal information processing module, which is used to collect statistics on historical wear information of machine tool tools , input historical data into the set artificial neural network, and carry out self-adaptive learning of the artificial neural network, pave the way for subsequent real-time pr...

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Abstract

The invention discloses a system and method for evaluating reliability of a machine tool. The system comprises a terminal information processing module, a data acquisition module, a vibration monitoring module, a microscopic optical module and an image processing module. Based on the self-learning and self-adaptive functions of an artificial neural network, historical data are used as a fitting sample to monitor performance parameter indexes affecting the reliability of the tool during the machining process in real time, such as vibration signals, current signals, sound wave signals, the wearing capacity and the processing roughness. By monitoring the running state of the tool in real time, feeding back real-time reliability information of the tool, and estimating the residual service lifeof the tool, a processing enterprise can make preventive measures in advance, the loss is reduced, and the overall processing efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of machine tool processing, and relates to a machine tool tool reliability evaluation system and method, in particular to a simple and efficient machine tool tool reliability evaluation system and method, which comprehensively considers machine tool historical processing data and processing The performance parameter index of the process realizes the evaluation of real-time reliability. Background technique [0002] With the continuous development of the modern manufacturing field, the machining process is gradually developing towards high efficiency and high precision. Especially the high-end CNC machine tools, which realize the high automation functions such as unmanned and intelligent processing. However, while the machining is unmanned, the reliability of the machining process of CNC machine tools must be guaranteed. [0003] Tool wear is an inevitable form of failure in the machining process. The most ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06N3/02
CPCG06N3/02G06Q10/06393
Inventor 陈乐王贤琳李卫飞王恺刘凯乐
Owner WUHAN UNIV OF SCI & TECH
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