Extreme value estimates using vibration energy harvesting

Joseph, George Vathakkattil; Hao, Guangbo; Pakrashi, Vikram

doi:10.1016/j.jsv.2018.08.045

Cited by 16 publications

(6 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is also representative of the ability to use established statistical markers for monitoring features of interest [31] in an edge setup. Previous research has also indicated that such markers can accommodate traditional, as well as new [32], types of sensors.…”

Section: Three-dimensional Plots Of Each Bolt-loosening Scenariomentioning

confidence: 99%

Edge Structural Health Monitoring (E-SHM) Using Low-Power Wireless Sensing

Buckley

Ghosh

Pakrashi

2021

Sensors

Self Cite

View full text Add to dashboard Cite

Effective Structural Health Monitoring (SHM) often requires continuous monitoring to capture changes of features of interest in structures, which are often located far from power sources. A key challenge lies in continuous low-power data transmission from sensors. Despite significant developments in long-range, low-power telecommunication (e.g., LoRa NB-IoT), there are inadequate demonstrative benchmarks for low-power SHM. Damage detection is often based on monitoring features computed from acceleration signals where data are extensive due to the frequency of sampling (~100–500 Hz). Low-power, long-range telecommunications are restricted in both the size and frequency of data packets. However, microcontrollers are becoming more efficient, enabling local computing of damage-sensitive features. This paper demonstrates the implementation of an Edge-SHM framework through low-power, long-range, wireless, low-cost and off-the-shelf components. A bespoke setup is developed with a low-power MEM accelerometer and a microcontroller where frequency and time domain features are computed over set time intervals before sending them to a cloud platform. A cantilever beam excited by an electrodynamic shaker is monitored, where damage is introduced through the controlled loosening of bolts at the fixed boundary, thereby introducing rotation at its fixed end. The results demonstrate how an IoT-driven edge platform can benefit continuous monitoring.

show abstract

Section: Three-dimensional Plots Of Each Bolt-loosening Scenariomentioning

confidence: 99%

Edge Structural Health Monitoring (E-SHM) Using Low-Power Wireless Sensing

Buckley

Ghosh

Pakrashi

2021

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…A probability distribution fit to observed data can often be a meaningful marker [59][60][61] for assessing various changes of damage conditions as compared to individual comparison of percentiles. Multiple distributions were considered for this data in this regard.…”

Section: Probability Distribution Fits For Acceleration Responsesmentioning

confidence: 99%

Damage Monitoring of a Catenary Moored Spar Platform for Renewable Energy Devices

2020

Self Cite

View full text Add to dashboard Cite

Structural performance of renewable energy device platforms is central to their power generation in a reliable and competitive manner. However, there is a gap in research in the conceptual and experimental stages of such devices at lower technological readiness levels in terms of understanding of their structural responses. Uncertainties around knowledge related to damage conditions of such structures are under-researched and experimental investigations into the monitoring of performance of such structures are significantly needed. This research addresses this need and investigates various damage conditions in a scaled catenary moored spar platform in an ocean wave basin, exposed to typical wave conditions for the west coast of Ireland. A comparison of the monitored structural responses was carried out with respect to the undamaged experimental model. It was observed that while free decay tests were not useful to distinguish between various damage levels, a characterisation of the distribution of the responses can be relevant in identifying damages or significant structural changes. The work contributes to the much-needed experimental evidence base around structural health monitoring of renewable energy device platforms.

show abstract

“…There is thus a need for a detailed numerical and experimental investigation of a relatively generic example which can be used in the future for similar studies, but also as an evidence base for current performance of patchbased energy harvesting and SHM, future adaption to new sensors, and to new structural systems and environments. This will also lend eventually to estimates on their lifetime risk levels [36] and comparative performances [37] around such levels, especially when the exposure is of a stochastic nature.…”

Section: Introductionmentioning

confidence: 97%

Numerical Analysis and Experimental Verification of Damage Identification Metrics for Smart Beam with MFC Elements to Support Structural Health Monitoring

Koszewnik

Lesniewski

Pakrashi

2021

Sensors

Self Cite

View full text Add to dashboard Cite

This paper investigates damage identification metrics and their performance using a cantilever beam with a piezoelectric harvester for Structural Health Monitoring. In order to do this, the vibrations of three different beam structures are monitored in a controlled manner via two piezoelectric energy harvesters (PEH) located in two different positions. One of the beams is an undamaged structure recognized as reference structure, while the other two are beam structures with simulated damage in form of drilling holes. Subsequently, five different damage identification metrics for detecting damage localization and extent are investigated in this paper. Overall, each computational model has been designed on the basis of the modified First Order Shear Theory (FOST), considering an MFC element consisting homogenized materials in the piezoelectric fiber layer. Frequency response functions are established and five damage metrics are assessed, three of which are relevant for damage localization and the other two for damage extent. Experiments carried out on the lab stand for damage structure with control damage by using a modal hammer allowed to verify numerical results and values of particular damage metrics. In the effect, it is expected that the proposed method will be relevant for a wide range of application sectors, as well as useful for the evolving composite industry.

show abstract

Extreme value estimates using vibration energy harvesting

Cited by 16 publications

References 28 publications

Edge Structural Health Monitoring (E-SHM) Using Low-Power Wireless Sensing

Edge Structural Health Monitoring (E-SHM) Using Low-Power Wireless Sensing

Damage Monitoring of a Catenary Moored Spar Platform for Renewable Energy Devices

Numerical Analysis and Experimental Verification of Damage Identification Metrics for Smart Beam with MFC Elements to Support Structural Health Monitoring

Contact Info

Product

Resources

About