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Online Tool Wear Monitoring of End Milling Cutters During High Speed Machining


Affiliations
1 Department of Mechanical Engineering, PSG College of Technology, Coimbatore, India
     

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High speed machining is a highly demanding technology for machining of complicated profiles and difficult to machine materials. Wear of a cutting tool in any machining operation is highly undesirable as it severely degrades the quality of machined surfaces and causes undesirable and unpredictable changes in work geometry. Therefore, an online toot wear monitoring system is essential for achieving the desired surface finish and also for automating the unmanned machines in the future. Acoustic emission based tool wear monitoring is one of the efficient method.
In this paper, the acoustic emission (AE) signals generated during high speed milling of aluminium using Titanium Aluminium Nitride (TiAIN) coated two flute end milling cutter is analyzed. The ischolar_main mean square values of the acquired signals are then correlated with the tool wear measured using Toolmaker's microscope. Finally, a relation between the tool wear and AE signal is established which is used for on-line tool wear monitoring, using regression and LabVIEW software.
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  • Online Tool Wear Monitoring of End Milling Cutters During High Speed Machining

Abstract Views: 216  |  PDF Views: 0

Authors

B. Giriraj
Department of Mechanical Engineering, PSG College of Technology, Coimbatore, India
R. Gandhinadhan
Department of Mechanical Engineering, PSG College of Technology, Coimbatore, India
V. Prabhu Raja
Department of Mechanical Engineering, PSG College of Technology, Coimbatore, India
R. Ganeshkumar
Department of Mechanical Engineering, PSG College of Technology, Coimbatore, India

Abstract


High speed machining is a highly demanding technology for machining of complicated profiles and difficult to machine materials. Wear of a cutting tool in any machining operation is highly undesirable as it severely degrades the quality of machined surfaces and causes undesirable and unpredictable changes in work geometry. Therefore, an online toot wear monitoring system is essential for achieving the desired surface finish and also for automating the unmanned machines in the future. Acoustic emission based tool wear monitoring is one of the efficient method.
In this paper, the acoustic emission (AE) signals generated during high speed milling of aluminium using Titanium Aluminium Nitride (TiAIN) coated two flute end milling cutter is analyzed. The ischolar_main mean square values of the acquired signals are then correlated with the tool wear measured using Toolmaker's microscope. Finally, a relation between the tool wear and AE signal is established which is used for on-line tool wear monitoring, using regression and LabVIEW software.