Abstract
A new concept for a smart drill spindle with active magnetic thrust bearing has been developed to enhance the monitoring and control capabilities of robotic drilling systems. This article reports on the realization and evaluation of an integrated thrust-force sensing technique for the spindle unit. The proposed technique uses a model-based state estimation scheme with calibrated nonlinear model of the spindle bearing forces. The method requires only one axial displacement sensor for real-time tool-force estimation and position control. A speed-dependent disturbance model is further defined and incorporated within the estimation scheme to compensate for spindle rotation effects. A method of using robot end-effector acceleration measurements to decouple the force estimate from both robot motion and gravity effects is also shown. Experiments are performed with a 7-axis lightweight industrial manipulator to assess the system's ability to provide accurate thrust force information under varied drilling conditions, while simultaneously controlling the motion of the drilling tool relative to the robot end-effector. The proposed technique provides new and important capabilities for drill-state recognition and penetration control, as well as the implementation of force-based control strategies.
| Original language | English |
|---|---|
| Pages (from-to) | 108-118 |
| Number of pages | 11 |
| Journal | IEEE/ASME Transactions on Mechatronics |
| Volume | 30 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2025 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Disturbance estimator
- drill state recognition
- force measurement
- magnetic bearing
- robot machining
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