Session: 05-01 Smart Sensors for SHM

Paper Number: 167846

167846 - Torque Sensing in Shafts Using a Quartz Tuning Fork Sensor 

Torque is a fundamental physical parameter in engineering, particularly in rotary systems such as transmission gearboxes, crankshafts, and gas turbine rotors. Accurate and reliable torque measurement is crucial for assessing structural health, optimizing power efficiency, and enhancing system dynamic performance. Over the years, various direct torque measurement techniques have been developed, including rotary, reaction, and contactless torque sensors, as well as surface acoustic wave sensors. While each of these methods offers distinct advantages, they also come with inherent limitations in terms of sensitivity, complexity, and adaptability to different environments.

This study introduces a novel torque sensing approach based on Quartz Tuning Fork (QTF) rosettes, which are strategically positioned at a 45-degree angle on the shaft surface. The QTF configuration consists of two tuning forks, each fixed at both ends to a small aluminum column. Under the influence of torsional loading, these tuning forks undergo longitudinal deformations and cause the frequency shifts, thereby enabling precise torque detection by monitoring frequency shifts. The unique arrangement allows for effective strain measurement in response to applied torque, offering a new pathway for high-sensitivity, real-time torque monitoring.

The experimental setup comprises a rotating shaft equipped with a lever for torque application and a commercial torque sensor for calibration and validation purposes. To further corroborate the effectiveness of the QTF-based method, two strain gauge rosettes were mounted adjacent to and parallel with the QTFs. The strain gauge measurements exhibited positive and negative strain shifts that were in direct agreement with the frequency behavior in the QTFs, reinforcing the reliability of the proposed sensing technique.

In addition to experimental validation, finite element simulations were conducted to model the stress-strain relationship under varying torque loads. These simulations provided further confirmation of the correlation between applied torque and measured strain, reinforcing the theoretical basis of the QTF sensing mechanism. The results demonstrate that the QTF-based sensor achieves a sensitivity of 5.98 Hz/N·m, making it a viable candidate for high-precision torque measurement.

The proposed method not only enables accurate real-time torque sensing in both rotational directions but also presents opportunities for future advancements. The compact and adaptable nature of QTFs suggests the potential for development into a wireless, multi-directional torque sensing system. Such a system could be beneficial in applications requiring non-intrusive, high-resolution torque monitoring, such as in industrial machinery, automotive powertrains, and aerospace engineering. The findings of this study highlight the effectiveness, reliability, and potential scalability of QTF-based torque sensing technology for real-world applications.

Presenting Author: haifeng zhang University of North Texas

Presenting Author Biography: Dr. Zhang is a Professor of the Department of Mechanical Engineering at the University of North Texas. He received his Ph.D. degree in Engineering Mechanics from University of Nebraska, Lincoln in 2007. He was a postdoctoral researcher in the Department of Material Science and Engineering in the Ohio State University before joining in University of North Texas in 2008. His research interests include advanced sensors, energy harvesters, structural health monitoring and ultrasonic nondestructive evaluation. Dr. Zhang has been the PI or a co-PI of $13M grants (his own share $5.6 M) from a variety of federal funding agencies (NSF, ARO, DoD, DOE, ARPA E, USDA, US Army) and industry. He has published more than 110 peer reviewed papers. He is the secretary for ASME Structural Health Monitoring technical committee, member of ASME Adaptive structure and materials branch and member of ASME website subcommittee of technical committee on vibration and sound.