TY - GEN
T1 - Optimal sensor configuration for fatigue life prediction in structural applications
AU - Khalil, Mohamed
AU - Kouroudis, Ioannis
AU - Wüchner, Roland
AU - Bletzinger, Kai Uwe
N1 - Publisher Copyright:
Copyright © 2019 ASME
PY - 2019
Y1 - 2019
N2 - Structural health monitoring is spreading widely across engineering domains. Its added value is not restricted to observing structural behavior, but crosses over to enabling the assessment of structural integrity under varying operating conditions. Damage prognosis is one vital demand from structural health monitoring solutions. Many methods have been developed to update damage predictions based on sensor data, nonetheless the selection and positioning of sensors to alleviate the prediction errors remains a question under investigation. In this work, an optimal sensor placement method is proposed for fatigue damage prediction in structures. An optimization problem is formulated to minimize the a-posteriori damage estimation error based on a Kalman filter. The derivation of the objective function is presented, along with a discussion of algorithm-related issues. Finally, the mentioned damage prediction approach is applied to two structures to verify the adequacy of the sensor configurations proposed by the method.
AB - Structural health monitoring is spreading widely across engineering domains. Its added value is not restricted to observing structural behavior, but crosses over to enabling the assessment of structural integrity under varying operating conditions. Damage prognosis is one vital demand from structural health monitoring solutions. Many methods have been developed to update damage predictions based on sensor data, nonetheless the selection and positioning of sensors to alleviate the prediction errors remains a question under investigation. In this work, an optimal sensor placement method is proposed for fatigue damage prediction in structures. An optimization problem is formulated to minimize the a-posteriori damage estimation error based on a Kalman filter. The derivation of the objective function is presented, along with a discussion of algorithm-related issues. Finally, the mentioned damage prediction approach is applied to two structures to verify the adequacy of the sensor configurations proposed by the method.
UR - http://www.scopus.com/inward/record.url?scp=85076431716&partnerID=8YFLogxK
U2 - 10.1115/DSCC2019-8909
DO - 10.1115/DSCC2019-8909
M3 - Conference contribution
AN - SCOPUS:85076431716
T3 - ASME 2019 Dynamic Systems and Control Conference, DSCC 2019
BT - Advanced Driver Assistance and Autonomous Technologies; Advances in Control Design Methods; Advances in Robotics; Automotive Systems; Design, Modeling, Analysis, and Control of Assistive and Rehabilitation Devices; Diagnostics and Detection; Dynamics and Control of Human-Robot Systems; Energy Optimization for Intelligent Vehicle Systems; Estimation and Identification; Manufacturing
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2019 Dynamic Systems and Control Conference, DSCC 2019
Y2 - 8 October 2019 through 11 October 2019
ER -