Date of Award

Winter 2011

Project Type


Program or Major

Mechanical Engineering

Degree Name

Master of Science

First Advisor

Todd Gross


As demand in the manufacturing sector increases, so does the need for greater process throughput and reduced component variability. These two objectives can be achieved by a process known as 'smart machining'. Smart machining utilizes sensors inside the machining environment to relay information to the machine controller. Most sensor systems adversely affect the machine dynamics, by reducing the machining envelope or reducing the machine's stiffness, or require physical connections to conditioning electronics. In this research, variables regarding a resonantly coupled wireless capacitive strain sensor were investigated. A parallel plate capacitive sensor prototype system yielded a strain sensitivity five times greater than analytical predictions. Experimental investigations were performed on probe design, sensor design, and application dynamics. Computer simulations were performed for the change in capacitance of an interdigitated comb capacitor for simplified loading cases. Finally, a simplified resonance detection circuit attached to the probe loop was designed, assembled, and successfully tested.