A review of structural health monitoring literature 1996-2001

By Charles R. Farrar, Jerry J. Czarnecki, Hoon Sohn, François M. Hemez. 2002

1,680 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e5c673e495d850bf490fbeb18d50a0eb4867d40b

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Citations in the corpus

Harvesting traffic-induced vibrations for structural health monitoring of bridges (2011, background): “There is a recognized need to monitor the health of civil, mechanical and aerospace structures [1].”
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights (2021, methodology): “Therefore, an accurate analytical model of the structure is required.(3) There are numerous works related to model-driven SHM.”
Simulation Methods for Guided Wave-Based Structural Health Monitoring: A Review (2015, background): “Since a complete review of signal processing techniques is not in the scope of the current article the interested reader is referred to [207, 236] and the references cited therein.”
An improved finite element model updating method by the global optimization technique 'Coupled Local Minimizers' (2008, unknown): “[3–7].”
The application of machine learning to structural health monitoring (2007, methodology): “The sequel to this survey is also available (Sohn et al. 2003) and shows that more research effort has been expended in the field between 1995 and 2001 than was expended up to 1995.”
A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications (2019, result): “Based on a similar idea, the work reported in [82] combined developments in modeling of fatigue-damage, isogeometric analysis of thin-shell structures [109], and structural health monitoring [110], to develop a computational steering framework for fatiguedamage prediction in full-scale laminated com”
Feasibility of using digital image correlation for unmanned aerial vehicle structural health monitoring of bridges (2018, background): “This research contributes to the overarching goal of developing a SHM system that can accurately monitor the condition of bridges, provide quantifiable measurement results, and minimize the interference with infrastructure functionality.”
Identification of isolated structural damage from incomplete spectrum information using l1-norm minimization (2014, unknown): “Since then, numerous analytical methods and experimental techniques have been developed in order to expand the limits of what can be detected by processing limited vibration measurements [6–10].”
Physics-guided Convolutional Neural Network (PhyCNN) for Data-driven Seismic Response Modeling (2019, unknown): “A comprehensive review of works on system identification and its applications in structural response modeling was given in [19–21].”
Automated detection of delamination and disbond from wavefield images obtained using a scanning laser vibrometer (2011, unknown): “integrity and safety of the structure being monitored [1, 2].”
Design of an FIR filter for the displacement reconstruction using measured acceleration in low‐frequency dominant structures (2010, background): “Dynamic responses of structural systems are frequently measured for the purpose of structural health monitoring (SHM) and structural control (SC) [1, 2].”
Delamination detection in composites through guided wave field image processing (2011, background): “In recent years, there has been an increasing demand for a structural health monitoring (SHM) that apprises users of the integrity and safety of the structure being monitored [1].”
Vibration-based monitoring of civil infrastructure: challenges and successes (2011, background): “Such assessments are necessarily non-destructive (since every structure is a prototype) and employ a wide range of non-destructive evaluation techniques [88].”