Damage degree prediction method of CFRP structure based on fiber Bragg grating and epsilon-support vector regression
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Prior researchers have demonstrated the successful application of the SVR algorithm within the area of composite structures.
“Notably, prior researchers have demonstrated the successful application of the SVR algorithm within the area of composite structures [52,53,65].”
From Machine Learning Algorithms for Prediction and Characterization of Cohesive Zone Parameters for Mixed-Mode Fracture (2024) · cites this paper as [53]
Cites
A tutorial on support vector regression
Smola, A. J., & Schölkopf, B. (2004) · Statistics and Computing · doi:10.1023/b:stco.0000035301.49549.88 · Cited by 13,482 · see citing works
Theoretical and Empirical Analysis of ReliefF and RReliefF
Robnik-Šikonja, M., & Kononenko, I. (2003) · Machine Learning · doi:10.1023/a:1025667309714 · Cited by 3,025 · see citing works
Intelligent health monitoring of aerospace composite structures based on dynamic strain measurements
Λούτας, Θ., Panopoulou, A., Roulias, D., et al. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.01.179 · Cited by 119 · see citing works
Khatir, S., Benaissa, B., Capozucca, R., et al. (2017) · Composite Structures · doi:10.1016/j.compstruct.2017.12.058 · Cited by 112 · see citing works
Support vector regression based metamodeling for seismic reliability analysis of structures
Ghosh, S., Roy, A., & Chakraborty, S. (2018) · Applied Mathematical Modelling · doi:10.1016/j.apm.2018.07.054 · Cited by 85 · see citing works
Jang, B.-W., & Kim, C. (2017) · Composites Part B Engineering · doi:10.1016/j.compositesb.2017.05.019 · Cited by 76 · see citing works
Research on FBG-Based CFRP Structural Damage Identification Using BP Neural Network
Geng, X., Lu, S., Jiang, M., et al. (2018) · Photonic Sensors · doi:10.1007/s13320-018-0466-0 · Cited by 71 · see citing works
Self-citationVibration-based delamination diagnosis and modelling for composite laminate plates
Cava, D. G., Palazzetti, R., Trendafilova, I. N., Fiorini, C., & Zucchelli, A. (2015) · Composite Structures · doi:10.1016/j.compstruct.2015.04.021 · Cited by 70 · see citing works
Frieden, J., Cugnoni, J., Botsis, J., & Gmür, T. (2011) · Composite Structures · doi:10.1016/j.compstruct.2011.08.025 · Cited by 59 · see citing works
Xiang, J., Liang, M., & He, Y. (2014) · Engineering Fracture Mechanics · doi:10.1016/j.engfracmech.2014.08.001 · Cited by 47 · see citing works
Nardi, D., Lampani, L., Pasquali, M., et al. (2016) · Composite Structures · doi:10.1016/j.compstruct.2016.02.005 · Cited by 47 · see citing works
Huang, B., Koh, B.-H., & Kim, H. S. (2014) · Computers & Structures · doi:10.1016/j.compstruc.2014.05.011 · Cited by 46 · see citing works
Medeiros, R. D., Sartorato, M., Vandepitte, D., et al. (2016) · Journal of Sound and Vibration · doi:10.1016/j.jsv.2016.06.047 · Cited by 42 · see citing works
A pattern recognition system based on acoustic signals for fault detection on composite materials
O’Brien, R., Fontana, J. M., Ponso, N., et al. (2017) · European Journal of Mechanics - A/Solids · doi:10.1016/j.euromechsol.2017.01.007 · Cited by 31 · see citing works
Sparse sensing detection of impact-induced delaminations in composite laminates
Gaudenzi, P., Nardi, D., Chiappetta, I., Atek, S., Lampani, L., Pasquali, M., Fabrizio Sarasini, A., Tirillò, J., & Valente, T. (2015) · Composite Structures · doi:10.1016/j.compstruct.2015.08.052 · Cited by 30 · see citing works
Khan, A., & Kim, H. S. (2018) · Composite Structures · doi:10.1016/j.compstruct.2018.08.014 · Cited by 30 · see citing works
Jang, B.-W., & Kim, C. (2018) · Composite Structures · doi:10.1016/j.compstruct.2018.01.095 · Cited by 20 · see citing works
Capozucca, R., & Magagnini, E. (2018) · Composite Structures · doi:10.1016/j.compstruct.2018.08.082 · Cited by 15 · see citing works
Multi-Damage Identification System of CFRP by Using FBG Sensors and Multi-Classification RVM Method
Lu, S., Jiang, M., Sui, Q., et al. (2015) · IEEE Sensors Journal · doi:10.1109/jsen.2015.2456333 · Cited by 10 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Ramian, A., & Elhajjar, R. (2024) · Journal of Composites Science · doi:10.3390/jcs8080326 · Cited by 8 · see citing works
“Furthermore, Lu et al. [53] utilized SVR to predict damage degrees in CFRP structures, highlighting its robustness in handling complex datasets.”
- Authors
- Lu, S., Jiang, M., Wang, X., Yu, H., & Su, C.
- Affiliations
- University of Jinan (CN)
- Shandong University (CN)
- Corresponding author
- Lu, Shizeng
- Venue
- Optik
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 180
- Pages
- 244-253
- ISSN
- 0030-4026 (ISSN-L)
- OpenAlex
- W2901317013
- Cited by
- 15
- References
- 19
- Citations by year
- 2024: 1 · 2023: 2 · 2022: 4 · 2021: 6 · 2020: 2
- FWCI
- 1.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Optik (publishedVersion)
- Funders
- National Natural Science Foundation of China (61803179, 41472260)
- Shandong Provincial Natural Science Foundation (ZR2017BF007)
- Young Scholars Program of Shandong University, China (2016WLJH30)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Fiber Optic Sensors
- Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
- Keywords
- carbon fiber reinforced polymer, fiber Bragg grating sensors, epsilon-support vector regression, structural health monitoring, Fourier transform features, dimensionality reduction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
