Study on High-Grade CNC Machine Tool Wear Monitoring Methods and Experimental System

Abstract:

Today, CNC machine tools are moving in the high-speed, high precision, heavy and complex processing of direction, leading to early failure in service due to machine performance, if not timely diagnosis and early warning, will result in waste increases, fluctuations in the quality, productivity decline.Therefore, to ensure reliable operation of CNC machine tools is very important.To build fault diagnosis of CNC machine tools and get test method as the goal, the tool wear experiments are carried out. Signals for cutting tool with different wear in milling process are detected，acquisited and analyzed through vibration sensors and acoustic emission sensors on the milling tools. To LabVIEW8.6 as development platform, a fault diagnosis experimental system of CNC machine tools is developed, including data acquisition module, signal analysis module, fault diagnosis module.

• Periodical: Advanced Materials Research (Volumes 591-593)
• Pages: 1844-1848
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.591-593.1844
• Online since: November 2012
• Authors: Min Huang, Xiu Li Liu, Le Yan
• Keywords: Acoustic Emission (AE), LabVIEW, Tool Wear, Vibration

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