Monitoring and Control System Design for Tool Wear Condition of CNC Machine Based on Artificial Neural Networks

Dan Su

doi:10.4028/www.scientific.net/AMM.556-562.3251

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Monitoring and Control System Design for Tool Wear...

Monitoring and Control System Design for Tool Wear Condition of CNC Machine Based on Artificial Neural Networks

Abstract:

Spindle wear of CNC machine affects the working efficiency of the machine. To solve this problem, the reasons for the generation of CNC machine tool equipment wear is analyzed, the system's hardware modules and software modules are designed and implemented in accordance with the system requirements. Parameters such as input and output power, spindle speed of CNC machine tool equipment are acquired by the sensor circuit. After a comprehensive analysis of the data, system software combined with neural network model displays the test results on the LCD screen, real-time output of CNC machine tool equipment operating status and the spindle wear. Thus the operation of CNC machine is ensured and equipment failure is avoided. Through the system test, indicating that the proposed system can real-time output the monitor results of spindle wear of CNC machine tool equipment, and has high measurement accuracy for the main parameters such as power and efficiency of the equipment.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

3251-3254

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.3251

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Cite this paper

Online since:

May 2014

Authors:

Dan Su*

Keywords:

Autonomous Detection, CNC Machine Tool, Spindle Wear

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* - Corresponding Author

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