A power harvester for wireless sensing applications

Casciati, Fabio; Rossi, Roberto

doi:10.1002/stc.179

Cited by 30 publications

(22 citation statements)

References 7 publications

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“…A super capacitor or rechargeable battery is usually employed as an energy storage element in energy harvesting. But a rechargeable battery is often preferable because of its higher power density and lower selfdischarge rate (Casciati and Rossi, 2007). It is not surprising that energy harvesting performance has been highlighted as a major index in the previous studies of EHC.…”

Section: Shen and Zhumentioning

confidence: 99%

Harvesting energy via electromagnetic damper: Application to bridge stay cables

Shen

Zhu

2014

Journal of Intelligent Material Systems and Structures

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Energy harvesting from ambient vibration is an emerging and promising solution to the power supply problem associated with autonomous sensors. This article proposes a novel strategy of harvesting damping energy from vibration control devices. A novel system, termed electromagnetic damper cum energy harvester, is employed to fulfill both vibration damping and energy harvesting functions. Electromagnetic damper cum energy harvester is essentially an electromagnetic device connected to a specially designed energy harvesting circuit, which is a buck-boost converter operating in a discontinuous conduction mode. The energy harvesting circuit can achieve satisfactory efficiency without any feedback loop. The effectiveness of the dual-function electromagnetic damper cum energy harvester is demonstrated through a numerical case study of bridge stay cables under wind excitations, in which the major parameters of electromagnetic damper cum energy harvester are determined through a simple design approach. Simulation results project average output power ranging from 82.5 to 2396.8 mW at a wind speed of 9-15 m/s, corresponding to an overall efficiency of 42.3%. The dual-function electromagnetic damper cum energy harvester also exhibits vibration control performance comparable to an optimally designed viscous fluid damper.

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Section: Shen and Zhumentioning

confidence: 99%

Harvesting energy via electromagnetic damper: Application to bridge stay cables

Shen

Zhu

2014

Journal of Intelligent Material Systems and Structures

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“…Therefore, if the wireless sensors are intended to be powered by batteries for a long monitoring period, both these two components should be power efficient. For this purpose, the possibility of harvesting power from the environment is forecasted to provide, in future, an effective solution to the limitations of batteries-supply [8]. On the other hand, for the applications that do not imply low-power requirements, the power consumption of the sensor requires a sufficient power output from the associated wireless sensing unit.…”

Section: A Power Managementmentioning

confidence: 99%

Frequency Division Multiplexing Wireless Connection

Casciati

Faravelli

Chen

2010

2010 International Conference on Computational Intelligence and Software Engineering

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In this paper, a newly designed wireless sensing network platform for structural monitoring applications is presented, and the results of a validation test performed in the authors' laboratory are reported. The main features offered by the proposed wireless platform are the capability of real-time and multi-channel data transmission, the high compatibility to different types of sensors, a highly efficient power-supply, and low-cost. Instead of adopting the most commonly used commercial wireless modems, the wireless communication is pursued by implementing an optimized and customized solution based on a recent System on Chip wireless transceiver. The Frequency Division Multiplexing method is exploited to ensure the real-time feature of the multi-channel data transmission. A simple and practical point-to-point topology is pursued. The usage of switching regulators which feature low quiescent current, highly efficient power conversion, an adjustable output voltage, and a high output power make this platform suitable for both low-power and non low-power structural monitoring applications involving different types of sensors. In order to validate the prototyped platform, a laboratory test is performed. The measurements of the acceleration response of a simple 3-storey structure mounted on a shaking table are acquired from both a wired DAQ system and the developed wireless platform. The data comparison enables to validate the efficacy of the realtime, multi-channel wireless transmission.

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“…Although technological solutions, such as energy harvesting and wireless power transmission , are promising and necessary in the future application of WSNs, they do not eliminate the entire challenge; thus, it is still crucial to develop new approaches to manage and minimize their power consumption. An idea that attracted many researchers after early application of wireless sensor network (WSN) in SHM was incorporating on‐board computational capability of wireless sensors in data processing .…”

Section: Introductionmentioning

confidence: 99%

Stochastic iterative modal identification algorithm and application in wireless sensor networks

Dorvash

Pakzad

2012

Struct. Control Health Monit.

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SUMMARY Computational capability of wireless sensor network (WSN) significantly facilitates application of dense sensory arrays, which is increasingly important in health monitoring of large‐scale structural systems. As the wireless sensor technology improves, more complicated tasks can be assigned to sensing units, and the communication between sensing nodes and their base station can be minimized, utilizing in‐network processing. This strategy should be used to address WSN challenges, such as limited communication bandwidth and prohibitive power consumption, associated with wireless communication and battery power. An iterative modal identification algorithm is proposed in this paper, which uses the on‐board processors for estimation of system parameters through iteration cycles. The iterative algorithm was originally developed such that each individual sensor, having an initial estimate of the system parameters, its local measurement, and the excitation signal, updates the estimated model and passes it through the network until convergence. This study further improves the algorithm to eliminate its limitations in need for availability of excitation load and initial estimate of the system parameters. As a result, the algorithm is applicable for modal identification of structural systems under ambient loading without need for prior information about the system parameters. The development of the algorithm is presented in this paper and validated through implementation on a numerically simulated example and a laboratory experiment. Furthermore, its performance is evaluated using data from an ambient vibration test of the Golden Gate Bridge using a WSN. Results of these implementations verify the functionality of the algorithm in monitoring of real‐life structural systems. Copyright © 2012 John Wiley & Sons, Ltd.

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A power harvester for wireless sensing applications

Cited by 30 publications

References 7 publications

Harvesting energy via electromagnetic damper: Application to bridge stay cables

Harvesting energy via electromagnetic damper: Application to bridge stay cables

Frequency Division Multiplexing Wireless Connection

Stochastic iterative modal identification algorithm and application in wireless sensor networks

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