Wednesday, April 11, 2018
10:15 a.m., 3405 Engineering Building
Refreshments Served at 10:00 a.m.
Faculty Round Table Discussion
Room 2555D Engineering Building
Nonlinear Dynamics and Vibrations in Monitoring Rotating Machinery and Energy Harvesting
Postdoctoral Research Associate
Center for Energy Harvesting Materials and Systems, Virginia Tech
Rapid industrial and technological developments continuously challenge the validity of traditional linear analyses and designs. In this talk, I will present two examples wherein novel technological developments motivate the need of nonlinear analyses and designs: vibration monitoring for cyclic symmetric rotor-bearing-housing systems and energy harvesting for sensor-embedded smart tires.
Wind turbines experience considerable coupled vibration between the blades and the tower. Such vibration could cause fatigue failures, thus motivating vibration analyses of entire rotor-bearing-housing systems. For a wind turbine, like many other rotating machinery, the rotor is cyclic symmetric, i.e., the rotors consist of N identical substructures repeating themselves in the circumferential direction each spanning an angle of 2π/N. Vibration mode shapes of a cyclic symmetric rotor are modulated by high-order harmonics from the cyclic symmetry; thus, characterization of the vibration signatures demands formidable computational efforts. In this talk, I will present the development of a reduced-order model that has the capability to predict ground-based response of rotor-bearing-housing systems of arbitrary geometry with the potential of in-situ structural health monitoring.
To improve vehicle safety, new tires that are internally installed with sensors to monitor road conditions in real time, known as smart tires, are under vigorous development. At least 30 mW is required for just one real-time sensor. Self-powered, energy harvesting sensors are essential to address the sharply rising power demands. However, the state-of-the-art energy harvesting methods, when applied to rotating tires, only generate around hundreds μW. In this talk, I will also present how scientific research in our lab led to the first 45 mW tire harvester with a half-power bandwidth of 52~111 km/h (32~69 mph), which utilizes stochastic resonance to amplify weak and noise road excitations and passively tunes the stochastic resonance frequency to track the time-varying driving speeds via a centrifugal stiffness effect. I will also present how self-powered smart tires can relate to research on autonomous and connected vehicles.
Dr. Wei-Che Tai is a postdoctoral research associate at the Center for Energy Harvesting Materials and Systems, Virginia Tech. He received his B.S. from National Taiwan University in 2007 and M.S. and Ph.D. from the University of Washington (UW) in 2012 and 2014, respectively, all in Mechanical Engineering. His research interests are in nonlinear vibrations and dynamics, multibody and rotor dynamics, smart structures and vibration energy harvesting. His research includes vibration monitoring of cyclic symmetric rotating machinery, snap-through instabilities of piezoelectric micro-actuators, broadband and self-tuning energy harvesting for biomechanical applications and rotating systems. He has authored eight grant proposals, including one award-winning ONR proposal. He also held a Lecturer position at UW, teaching dynamics and kinematics courses, and has served as a reviewer of the Journal of Vibration and Acoustics and IEEE/ASME Transactions on Mechatronics, and served as a session chair for the ASME IDETC/CIE 2018.