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  5. Energy Harvesting Techniques for Health Monitoring and Indicators for Control of a Damaged Pipe Structure

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Article
en
2018

Energy Harvesting Techniques for Health Monitoring and Indicators for Control of a Damaged Pipe Structure

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en
2018
Vol 21 (3)
Vol. 21
DOI: 10.12989/sss.2018.21.3.287dspace.kci.go.kr/handle/kci/517768?show=f…

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Satish Nagarajaiah
Satish Nagarajaiah

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Paul Cahill
Vikram Pakrashi
Peng Sun
+2 more

Abstract

Applications of energy harvesting from mechanical vibrations is becoming popular but the full potential of such applications is yet to be explored. This paper addresses this issue by considering an application of energy harvesting for the dual objective of serving as an indicator of structural health monitoring (SHM) and extent of control. Variation of harvested energy from an undamaged baseline is employed for this purpose and the concept is illustrated by implementing it for active vibrations of a pipe structure. Theoretical and experimental analyses are carried out to determine the energy harvesting potential from undamaged and damaged conditions. The use of energy harvesting as indicator for control is subsequently investigated, considering the effect of the introduction of a tuned mass damper (TMD). It is found that energy harvesting can be used for the detection and monitoring of the location and magnitude of damage occurring within a pipe structure. Additionally, the harvested energy acts as an indicator of the extent of reduction of vibration of pipes when a TMD is attached. This paper extends the range of applications of energy harvesting devices for the monitoring of built infrastructure and illustrates the vast potential of energy harvesters as smart sensors.

How to cite this publication

Paul Cahill, Vikram Pakrashi, Peng Sun, A. Mathewson, Satish Nagarajaiah (2018). Energy Harvesting Techniques for Health Monitoring and Indicators for Control of a Damaged Pipe Structure. , 21(3), DOI: https://doi.org/10.12989/sss.2018.21.3.287.

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Publication Details

Type

Article

Year

2018

Authors

5

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.12989/sss.2018.21.3.287

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