Early damage assessment in large-scale structures by innovative statistical pattern recognition methods based on time series modeling and novelty detection
Time series analysis and novelty detection are effective and promising methods for data-
driven structural health monitoring (SHM) based on the statistical pattern recognition …
driven structural health monitoring (SHM) based on the statistical pattern recognition …
Sensor placement algorithm for structural health monitoring with redundancy elimination model based on sub-clustering strategy
Considering the limitation of selecting several neighbor sensors in a local region similar to
just single one, namely redundant information, a sensor placement algorithm for structural …
just single one, namely redundant information, a sensor placement algorithm for structural …
Data-driven probabilistic quantification and assessment of the prediction error model in damage detection applications
NE Silionis, KN Anyfantis - Probabilistic Engineering Mechanics, 2023 - Elsevier
Advances in computer hardware and sensor technologies have led to a surge in the use of
data-driven modeling and machine learning for structural engineering applications, with …
data-driven modeling and machine learning for structural engineering applications, with …
Optimal sensor configuration for ultrasonic guided-wave inspection based on value of information
Condition-based maintenance critically relies on efficient and reliable structural health
monitoring systems, where the number, position and type of sensors are determined …
monitoring systems, where the number, position and type of sensors are determined …
Optimal sensor and actuator placement for structural health monitoring via an efficient convex cost-benefit optimization
The number and position of sensors and actuators are key decision variables that dictate the
performance of any structural health monitoring system. This paper proposes choosing them …
performance of any structural health monitoring system. This paper proposes choosing them …
Lichtenberg optimization algorithm applied to crack tip identification in thin plate-like structures
Purpose This study aims to develop a numerical identification and characterization of crack
propagation through the use of a new optimization metaheuristics called Lichtenberg …
propagation through the use of a new optimization metaheuristics called Lichtenberg …
Bayesian optimal sensor placement for parameter estimation under modeling and input uncertainties
T Ercan, C Papadimitriou - Journal of Sound and Vibration, 2023 - Elsevier
A Bayesian optimal sensor placement (OSP) framework for parameter estimation in
nonlinear structural dynamics models is proposed, based on maximizing a utility function …
nonlinear structural dynamics models is proposed, based on maximizing a utility function …
On statistical Multi-Objective optimization of sensor networks and optimal detector derivation for structural health monitoring
L Colombo, MD Todd, C Sbarufatti, M Giglio - Mechanical Systems and …, 2022 - Elsevier
Sensor placement and structural health classifiers are fundamental components of Structural
Health Monitoring (SHM) systems, as they largely define system detection (or classification) …
Health Monitoring (SHM) systems, as they largely define system detection (or classification) …
[HTML][HTML] Systematic sensor placement for structural anomaly detection in the absence of damaged states
C Bigoni, Z Zhang, JS Hesthaven - Computer Methods in Applied …, 2020 - Elsevier
In structural health monitoring (SHM), risk assessment and decision strategies rely primarily
on sensor responses. Simulated data can be generated to emulate the monitoring …
on sensor responses. Simulated data can be generated to emulate the monitoring …
A probabilistic optimal sensor design approach for structural health monitoring using risk-weighted f-divergence
This paper presents a new approach to optimal sensor design for structural health
monitoring (SHM) applications using a modified f-divergence objective functional. One of the …
monitoring (SHM) applications using a modified f-divergence objective functional. One of the …