Optimal location of a fiber-optic-based sensing net for SHM applications using a digital twin

I. Kressel; U. Ben-Simon; S. Shoham; G. Don-Yehiya; S. Sheinkman; R. Davidi; M. Tur

Optimal location of a fiber-optic-based sensing net for SHM applications using a digital twin

I. Kressel, U. Ben-Simon, S. Shoham, G. Don-Yehiya, S. Sheinkman, R. Davidi, M. Tur

School of Electrical Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

A strain-based sensing concept for SHM applications has the important advantage that on-ground and in-flight measurements can be directly correlated with the results of structural stress/strain finite element (FE) analysis. In the current work, a detailed FE model of unmanned aerial vehicle (UAV) has been calibrated against actual ground test measurements, as obtained by a fiber-optic sensing net, to be later used as a digital twin platform for optimizing sensors locations for sensitive damage detection. The use of a digital twin for damage detection should prove to be a cost-effective approach for optimizing an SHM damage detection system.

Original language	English
State	Published - 2018
Event	9th European Workshop on Structural Health Monitoring, EWSHM 2018 - Manchester, United Kingdom Duration: 10 Jul 2018 → 13 Jul 2018

Conference

Conference	9th European Workshop on Structural Health Monitoring, EWSHM 2018
Country/Territory	United Kingdom
City	Manchester
Period	10/07/18 → 13/07/18

Cite this

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title = "Optimal location of a fiber-optic-based sensing net for SHM applications using a digital twin",

abstract = "A strain-based sensing concept for SHM applications has the important advantage that on-ground and in-flight measurements can be directly correlated with the results of structural stress/strain finite element (FE) analysis. In the current work, a detailed FE model of unmanned aerial vehicle (UAV) has been calibrated against actual ground test measurements, as obtained by a fiber-optic sensing net, to be later used as a digital twin platform for optimizing sensors locations for sensitive damage detection. The use of a digital twin for damage detection should prove to be a cost-effective approach for optimizing an SHM damage detection system.",

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TY - CONF

T1 - Optimal location of a fiber-optic-based sensing net for SHM applications using a digital twin

AU - Kressel, I.

AU - Ben-Simon, U.

AU - Shoham, S.

AU - Don-Yehiya, G.

AU - Sheinkman, S.

AU - Davidi, R.

AU - Tur, M.

PY - 2018

Y1 - 2018

N2 - A strain-based sensing concept for SHM applications has the important advantage that on-ground and in-flight measurements can be directly correlated with the results of structural stress/strain finite element (FE) analysis. In the current work, a detailed FE model of unmanned aerial vehicle (UAV) has been calibrated against actual ground test measurements, as obtained by a fiber-optic sensing net, to be later used as a digital twin platform for optimizing sensors locations for sensitive damage detection. The use of a digital twin for damage detection should prove to be a cost-effective approach for optimizing an SHM damage detection system.

AB - A strain-based sensing concept for SHM applications has the important advantage that on-ground and in-flight measurements can be directly correlated with the results of structural stress/strain finite element (FE) analysis. In the current work, a detailed FE model of unmanned aerial vehicle (UAV) has been calibrated against actual ground test measurements, as obtained by a fiber-optic sensing net, to be later used as a digital twin platform for optimizing sensors locations for sensitive damage detection. The use of a digital twin for damage detection should prove to be a cost-effective approach for optimizing an SHM damage detection system.

UR - http://www.scopus.com/inward/record.url?scp=85070869195&partnerID=8YFLogxK

M3 - הרצאה

AN - SCOPUS:85070869195

Y2 - 10 July 2018 through 13 July 2018

ER -

Optimal location of a fiber-optic-based sensing net for SHM applications using a digital twin

Abstract

Conference

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