A State-of-the-Art Review on FRF-Based Structural Damage Detection: Development in Last Two Decades and Way Forward
International Journal of Structural Stability and Dynamics, ISSN: 1793-6764, Vol: 22, Issue: 2
2022
- 42Citations
- 22Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Review Description
Vibration-based damage detection techniques receive wide attention of the research community in recent years to overcome the limitations of conventional structural health monitoring methods. The modal parameters, namely, natural frequencies, mode shapes, transmissibility, frequency response function (FRF), and other damage sensitive features are usually employed to identify damage in a structure. The main objective of this review is to generate a detailed understanding of FRF-based techniques and to study their performance in terms of advantage, accuracy, and limitations in structural damage detection. This paper also reviews various approaches to develop methodologies in terms of efficiency and computational time. The study observed that excitation frequency, location of application of excitation, type of sensor, number of measurement locations, noise contamination in FRF data, selection of frequency range for simulation, weighting and numerical techniques to solve the over-determined set of equations influence the effectiveness of damage identification procedure. Limitations and future prospects have also been addressed in this paper. The content of this paper aims to guide researchers in developing formulations, updating models, and improving results in the field of FRF-based damage identification.
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