An experiment was set up at the University of Tennessee Knoxville (UTK) to test methods for estimating the cutting forces in real time within machine tools for any spindle speed, force profile, tool type, and cutting conditions. Before cutting, a metrology suite and instrumented tool holder were used to induce magnetic forces during spindle rotation, while on-machine vibrations, magnetic forces, and error motions were measured for various combinations of speeds and forces. A model may then relate the measured accelerations to the forces, such that during cutting, on-machine measured vibrations may be used in the model to estimate the cutting forces in real time. To test this process, the metrology suite and the instrumented tool holder were removed, except that the on-machine accelerometers remained. A dynamometer was then set up on the worktable with a workpiece to independently measure cutting forces during machining. Various cutting passes were performed with different mills while the dynamometer data and accelerometer data were collected. Even though considerable research has been conducted to estimate cutting forces with accelerometers and measured FRFs, one main challenge remains: a method must be created to estimate the cutting forces in real-time for any spindle speed, force profile, tool type, and cutting conditions. This dataset can be used to develop or advance such methods for industrial adoption.
About this Dataset
Title | Cutting Force Monitoring Experiment 01 |
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Description | An experiment was set up at the University of Tennessee Knoxville (UTK) to test methods for estimating the cutting forces in real time within machine tools for any spindle speed, force profile, tool type, and cutting conditions. Before cutting, a metrology suite and instrumented tool holder were used to induce magnetic forces during spindle rotation, while on-machine vibrations, magnetic forces, and error motions were measured for various combinations of speeds and forces. A model may then relate the measured accelerations to the forces, such that during cutting, on-machine measured vibrations may be used in the model to estimate the cutting forces in real time. To test this process, the metrology suite and the instrumented tool holder were removed, except that the on-machine accelerometers remained. A dynamometer was then set up on the worktable with a workpiece to independently measure cutting forces during machining. Various cutting passes were performed with different mills while the dynamometer data and accelerometer data were collected. Even though considerable research has been conducted to estimate cutting forces with accelerometers and measured FRFs, one main challenge remains: a method must be created to estimate the cutting forces in real-time for any spindle speed, force profile, tool type, and cutting conditions. This dataset can be used to develop or advance such methods for industrial adoption. |
Modified | 2023-05-17 00:00:00 |
Publisher Name | National Institute of Standards and Technology |
Contact | mailto:[email protected] |
Keywords | Smart manufacturing , Industry 4.0 , Data-driven dynamics , Frequency response function , Machine tool , Modeling , Dynamics , Machining processes , Sensing , Monitoring , Diagnostics |
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