An introduction to structural health monitoring

By Charles R. Farrar, Keith Worden. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2007

2,934 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/5d675f4961a593584641871f91f29927e61af357

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Citations in the corpus

Infrared thermography for condition monitoring – A review (2013, background): “For aerospace, civil and mechanical engineering infrastructure industries, the process of implementing a damage identification strategy for condition monitoring is known as structural health monitoring (SHM) where damages are defined as changes to the material and geometric properties [2].”
A framework for quantifying the value of vibration-based structural health monitoring (2022, background): “In designing a case-specific SHM system, one should start by defining the specific target structure and the associated damages that one pursues to detect with this system [4].”
Structural health monitoring: Closing the gap between research and industrial deployment (2018, methodology): “The tests also identified uniqueness issues associated with the damage prediction if only resonance frequencies are used, and this lack of success led to the oil industry abandoning the technology in the mid 1980s.(13) There has been a great deal of further work since that time and many reviews, for”
Overview of Fiber Optic Sensor Technologies for Strain/Temperature Sensing Applications in Composite Materials (2016, background): “The diagnostics process and condition monitoring of composite structures is usually carried out during their working life [2].”
Review of Bridge Structural Health Monitoring Aided by Big Data and Artificial Intelligence: From Condition Assessment to Damage Detection (2020, neutral): “Aktan et al. (1996) proposed that SHM should be considered within the realm of condition assessment; Farrar and Worden (2007) regarded SHM as a damage detection process.”
Materials that couple sensing, actuation, computation, and communication (2015, background): “Modal features are useful for detecting defects in structures [30, 70].”
Corrosion Protection Systems and Fatigue Corrosion in Offshore Wind Structures: Current Status and Future Perspectives (2017, methodology): “The approach should be implemented considering a four stage procedure [75]:”
Bolt loosening analysis and diagnosis by non-contact laser excitation vibration tests (2013, methodology): “The process to implement a method of damage detection is generally referred to as structural health monitoring [6].”
Strategies for Guided Wave Structural Health Monitoring (2007, background): “A number of strategies for SHM have been investigated (Farrar & Worden 2007), and Boller (2000) indicates how they can be integrated into a system.”
Identification of cracks in thin-walled structures by means of wavenumber filtering (2015, methodology): “Recent developments in SHM include applications of acousto-ultrasonics and guided waves for damage identification [3].”
Self-sensing piezoresistive cement composite loaded with carbon black particles (2017, background): “2 The development of SHM has enabled a more effective evaluation of the stresses/deformations that take place in buildings, bridges and dams, for instance [1, 2].”
Structural Health Monitoring Framework Based on Internet of Things: A Survey (2017, methodology): “Since raw data from sensors are unreliable and noisy, data stored in CouchDB are extracted and preprocessed in order to remove noise and be reorganized before processing task [40], [73].”
A review of damage detection methods for wind turbine blades (2015, background): “Damage can be counted as changes to the material and/or geometric properties of a structure, including variations to the boundary conditions and structural connectivity, which can adversely affect designed structural functions and performance (Farrar and Worden 2007).”
Digital twin, physics-based model, and machine learning applied to damage detection in structures (2020, background): “…disciplines are part of a digital twin framework; for example, ﬁnite element model [19], neural networks [5], digital signal processing [20], structural health monitoring [21], uncertainty quantiﬁcation [22], inverse problem [23], model up-dating [24], and veriﬁcation and validation [25].”