Abstract
Nowadays, the trend of milling technique is high speed machining. Plunge milling is one of the most efficient machining with high metal removal rate. The online monitoring of tool wear has been the key of plunge milling process. In this paper, the technique of tool wear monitoring in plunge milling process was studied. An online monitoring and faults diagnosis system based on PC104 bus and Lab VIEW was established. The system can acquire and analyze the vibration signals by acceleration sensors that were put in the milling tool holder. The model between the tool wear and vibration signals in plunge milling 45# steel was built by fitting of multivariable linear regression on the base of experiment. The model was realized on the open NC system, monitoring the tool wear degree quantificational. Through the verification to experiment data, the model was effective and reliable, and the error of forecast tool wear value was within 10% by the tool wear model. The model provided an important reference for the research of tool wear on the plunge milling.
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