Performance evaluation of twin piezoelectric wind energy harvesters under mutual interference

Hu, Gang; Wang, Junlei; Su, Zhen; Li, Guoping; Peng, H.Y.; Kwok, K.C.S.

doi:10.1063/1.5109457

Cited by 116 publications

(40 citation statements)

References 30 publications

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“…1 The advantage of energy harvesting lies in its sustainability and beneficial avoidance of battery replacement. 2,3 Harvesting environmental vibrations can be generally divided into two categories, that is, the preexisting base excitations resulting from the motion of machinery, structures, or human movements 4,5 and the flow-induced vibrations due to aeroelastic instabilities, such as vortexinduced vibration (VIV), 6 galloping, 7,8 flutter, 9,10 and buffeting, 11 or their synergetic effect. 12,13 Wind energy is a steady and pervasive power source in the environment.…”

Section: Discussionmentioning

confidence: 99%

Equivalent circuit representation of a vortex‐induced vibration‐based energy harvester using a semi‐empirical lumped parameter approach

et al. 2020

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Summary Small‐scale wind energy harvesting from vortex‐induced vibrations (VIV) has been introduced in recent years as a renewable power source for microelectronics and wireless sensors. Previous studies have focused on modeling and optimizing the VIV‐based piezoelectric energy harvester (VIVPEH) structures and simplified the complicated interface circuits as pure resistors with an alternating current (AC) output. In practice, an AC output is required to be transformed into a direct current (DC) followed by further regulations before being used for real applications. Incorporating the rectification and regulation, traditional theoretical and numerical models will become extremely cumbersome and even impossible. To address this issue, this work proposes an equivalent circuit model (ECM) for a typical VIVPEH. The Scanlan‐Ehsan aerodynamic force model is employed to describe the fluid‐structure interaction. Wind tunnel experiments are carried out to validate the derived model. The performances of the VIVPEH with AC and DC interface circuits are subsequently analyzed and compared to understand the influences of these circuits on the operational wind speed bandwidth, power output, vibration amplitude, and electrical damping.

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Section: Discussionmentioning

confidence: 99%

Equivalent circuit representation of a vortex‐induced vibration‐based energy harvester using a semi‐empirical lumped parameter approach

et al. 2020

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“…In the past two decades, the piezoelectric energy scavenging technology has been an ever-increasing focus due to its potential for letting micro-electro-mechanical systems (MEMS) [1][2][3][4][5][6][7] to get rid of chemical batteries. This technology can be an alternative of the chemical batteries that require to be frequently recharged or replaced from the sensors and devices.…”

Section: Introductionmentioning

confidence: 99%

Bluff body with built‐in piezoelectric cantilever for flow‐induced energy harvesting

Zhang

Wang

2020

Int J Energy Res

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Summary This paper investigates a flow‐induced vibration energy harvester comprising a piezoelectric beam (piezo‐beam) installed within a hollow circular cylinder. Under the flow excitation, the energy‐harvesting system including the cylinder and the piezo‐beam vibrates and generates electricity. A lumped parametric model incorporating the fluid‐structure interaction (FSI) is developed to evaluate the performance of the proposed energy harvester. Based on the theoretical analysis, several guidelines on the design and optimization of the proposed energy harvester are provided. Subsequently, a numerical model is used to simulate the FSI between the proposed system and the external flow field. Finally, a physical prototype is fabricated and an experiment is conducted to test the actual performance for validation. The theoretical analysis results are verified by the numerical and experimental results.

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“…is interesting nonlinear phenomenon makes it possible for the weak signals to strengthen their intensities by absorbing a certain fraction of the noise energy, thus highlighting the weak signals [8,9]. SR has attracted much attention from the physics and engineering community in the research areas such as dynamical nonlinearity [10][11][12], structure monitoring [13], and energy harvesting [14][15][16]. Moreover, in view of the good performance of SR using noise to enhance periodic signal features, SR-based weaksignal detection and fault diagnosis methods have been investigated and successfully applied in rolling bearing fault diagnosis [17,18].…”

Section: Introductionmentioning

confidence: 99%

Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance

Lai

Wang

Zhang

et al. 2020

Shock and Vibration

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The weak-signal detection technologies based on stochastic resonance (SR) play important roles in the vibration-based health monitoring and fault diagnosis of rolling bearings, especially at their early-fault stage. Aiming at the parameter-fixed vibration signals in practical engineering, it is feasible to diagnose the potential rolling bearing faults through adaptively adjusting the SR system parameters, as well as other generalized parameters such as the amplitude-transformation coefficient and scale-transformation coefficient. However, extant adaptive adjustment methods focus on the system parameters, while the adjustments of other adjustable parameters have not been fully studied, thus limiting the detection performance of the adaptive SR method. In order to further enhance the detection performance of adaptive SR methods and extend their application in rolling bearing fault diagnosis, an adaptive multiparameter-adjusting SR (AMPASR) method for bistable systems based on particle swarm optimization (PSO) algorithm is proposed in this paper. This method can produce optimal SR output through adaptively adjusting multiparameters, thus realizing fault feature extraction and further fault diagnosis. Furthermore, the influence of algorithm parameters on the optimization results is discussed, and the optimization results of the Langevin system and the Duffing system are compared. Finally, we propose a weak-signal detection method based on the AMPASR of the Duffing system and employ three diagnosis examples involving inner ring fault, outer ring fault, and rolling element fault diagnoses to demonstrate its feasibility in rolling bearing fault diagnosis.

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Performance evaluation of twin piezoelectric wind energy harvesters under mutual interference

Cited by 116 publications

References 30 publications

Equivalent circuit representation of a vortex‐induced vibration‐based energy harvester using a semi‐empirical lumped parameter approach

Equivalent circuit representation of a vortex‐induced vibration‐based energy harvester using a semi‐empirical lumped parameter approach

Bluff body with built‐in piezoelectric cantilever for flow‐induced energy harvesting

Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance

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