Doctoral Dissertations

Date of Award

5-2024

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Mechanical Engineering

Major Professor

Tony L. Schmitz

Committee Members

Bradley H. Jared, Tony Z. Shi, Michael F. Gomez

Abstract

This research focuses on the design, development, and testing of a low-cost, table-mounted drilling torque and thrust force dynamometer. A two degree of freedom design, based on constrained-motion flexure-based kinematics is implemented. The drilling torque and thrust force are inferred from displacement measurements using a novel dual-magnet Hall effect sensor configuration. The constrained-motion drilling dynamometer (CMDD) consists of both rotationally and translationally compliant flexure elements. During drilling, the rotational motion of the CMDD mounting stage is measured using two Hall effect sensors. The translational displacement is measured with a second set of Hall effect sensors. The Hall effect sensors output voltage is used to represent the corresponding displacements. The measured rotational and translational motions are combined with the dynamometer stiffness values to infer the drilling torque and thrust force. To validate the CMDD performance, a prototype is fabricated and evaluated in comparison to a commercially available, piezoelectric-based force/torque dynamometer. A novel method for tool wear detection is demonstrated, where the tool wear is determined based on the increase of drilling torque and thrust force of an aluminum witness sample fixed to the CMDD.

This research will contribute to the state-of-the-art by providing a reliable, low-cost, constrained-motion dynamometer for drilling torque and thrust force measurement. The two degree of freedom, flexure-based design for simultaneous torque and thrust force measurement and dual-magnet Hall effect sensor arrangement provide an innovative and low-cost dynamometer for both research and production settings. The CMDD offers significant improvements to machine monitoring capabilities by providing advancements to process parameter optimization, tool condition monitoring, improved process modeling capabilities, and chatter detection, while also serving as a low-cost alternative to commercially available solutions.

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