Energy harvesting from the rotating system has been an influential topic for researchers over the past several years. Yet, most of these harvesters are linear resonance-based harvesters whose output power drops dramatically under random excitations. This poses a serious problem because a lot of vibrations in rotating systems are stochastic. In this dissertation, a novel energy harvesting strategy for rotating systems was proposed by taking advantage of stochastic resonance. Stochastic resonance is referred to as a physical phenomenon that is manifest in nonlinear bistable systems whereby a weak periodic signal can be significantly amplified with the aid of inherent noise or vice versa. Stochastic resonance can thus be used to amplify the noisy and weak vibration motion.
Through mathematical modeling, this dissertation shows that stochastic resonance is particularly favorable to energy harvesting in rotating systems. The conditions for stochastic resonance are satisfied by adding a nonlinear bistable energy harvester to the rotating system because whirl noise and periodic signală„´ already coexist in the rotating environment. Both numerical and experimental results show that stochastic resonance energy harvester has higher power and wider bandwidth than linear harvesters under a rotating environment.
The dissertation also investigates how stochastic resonance changes for the various types of excitation that occur in real-world applications. Under the non-gaussian noise, the stochastic resonance frequency is shifted larger value. Furthermore, the co-existence of the vibrational and stochastic resonance is observed depending on the periodic signal to noise ratio.
The dissertation finally proposed two real applications of stochastic resonance energy harvesting. First, stochastic resonance energy harvester for oil drilling applications is presented. In the oil drilling environment, the periodic force in rotating shafts is biased, which can lower the efficacy of stochastic resonance. To solve the problem, an external magnet was placed above the bi-stable energy harvester to compensate for the biased periodic signal. Energy harvester for smart tires is also proposed. The passively tuned system is implemented in a rotating tire via centrifugal force. An inward-oriented rotating beam is used to induce bistability via the centrifugal acceleration of the tire. The results show that larger power output and wider bandwidth can be obtained by applying the proposed harvesting strategy to the rotating system. / Doctor of Philosophy / In this dissertation, a novel energy harvesting strategy for rotating systems was proposed by taking advantage of stochastic resonance. Stochastic resonance is referred to as a physical phenomenon that is manifest in nonlinear bistable systems whereby a weak periodic signal can be significantly amplified with the aid of inherent noise or vice versa. Stochastic resonance can thus be used to amplify the noisy and weak vibration motion.
Through mathematical modeling, this dissertation shows that stochastic resonance is particularly favorable to energy harvesting in rotating systems.Both numerical and experimental results show that stochastic resonance energy harvester has higher power and wider bandwidth than linear harvesters under a rotating environment.
The dissertation also investigates how stochastic resonance changes for the various types of excitation that occur in real-world applications.
The dissertation finally proposed two real applications of stochastic resonance energy harvesting. First, stochastic resonance energy harvester for oil drilling applications is presented. Energy harvester for smart tires is also proposed. The results show that larger power output and wider bandwidth can be obtained by applying the proposed harvesting strategy to the rotating system.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/96728 |
| Date | 05 February 2020 |
| Creators | Kim, Hongjip |
| Contributors | Mechanical Engineering, Zuo, Lei, Hajj, Muhammad R., Furukawa, Tomonari, Parker, Robert G. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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