PSI - Issue 52

Yuhang Pan et al. / Procedia Structural Integrity 52 (2024) 699–708 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

708 10

the mean value of MND predicted based on PCA-FRF is 2.05 cm and the minimum value is 1.18 cm. For the hybrid method, the predicted average MND value is 0.79 cm and the minimum MND value is 0.38cm, which verifies the effectiveness of the hybrid method proposed in this research. In addition, the damage used in current research is by adding mass, future work will be dedicated to the validation of the proposed method using actual damage. Subsequently, this method will be applied to real-world scenarios, with real damage and on more some more complex structures.

References

Bandara, R. P., Chan, T. H., Thambiratnam, D. P., 2014. Structural damage detection method using frequency response functions. Structural Health Monitoring, 13(4), 418 – 429. Castellini, P., Marco Revel, G., 2000. Experimental technique for structural diagnostic based on laser vibrometry and neural networks. Shock and Vibration, 7(6), 381 – 397. Fan, W., Qiao, P., 2011. Vibration-based damage identification methods: A review and comparative study. Structural Health Monitoring, 10(1), 83 – 111. Giannakeas, I. N., Sharif Khodaei, Z., & Aliabadi, M. H., 2023. An up-scaling temperature compensation framework for guided wave – based structural health monitoring in large composite structures. Structural Health Monitoring, 22(2), 777 – 798. Huang, T., Chaves-Vargas, M., Yang, J., Schröder, K.-U., 2016. A baseline-free damage detection method based on node displacement in mode shape, 8th European Workshop on Structural Health Monitoring. Bilbao, Spain. Khan, A., Ko, D. K., Lim, S. C., Kim, H. S., 2019. Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network. Composites Part B: Engineering, 161, 586 – 594. Kralovec, C., Schagerl, M., 2020. Review of Structural Health Monitoring Methods Regarding a Multi-Sensor Approach for Damage Assessment of Metal and Composite Structures. Sensors, 20(3), 826. Minak, G., Palazzetti, R., Trendafilova, I., Zucchelli, A., 2010. Localization of a delamination and estimation of its length in a composite laminate beam by the VSHM and pattern recognition methods. Mechanics of Composite Materials, 46(4), 387 – 394. Nayyar, A., Baneen, U., Ahsan, M., Zilqurnain Naqvi, S. A., Israr, A., 2022. Damage detection based on output-only measurements using cepstrum analysis and a baseline-free frequency response function curvature method. Science Progress, 1, 1 – 25. Negru, I., Gillich, G. R., Praisach, Z. I., Tufoi, M., Gillich, N., 2015. Natural frequency changes due to damage in composite beams. Journal of Physics: Conference Series, 628(1), 012091. Pan, Y., Qiao, Y., Wang, Y., Liu, X., Zhou, P., 2023. Real-time prediction of grinding surface roughness based on multi-sensor signal fusion. The International Journal of Advanced Manufacturing Technology 2023, 1 – 15. Pan, Y., Wang, Y., Zhou, P., Yan, Y., Guo, D., 2020. Activation functions selection for BP neural network model of ground surface roughness. Journal of Intelligent Manufacturing, 31(8), 1825 – 1836. Qing, X., Liao, Y., Wang, Y., Chen, B., Zhang, F., Wang, Y., 2022. Machine Learning Based Quantitative Damage Monitoring of Composite Structure,13(2), 167-202. Ren, F., Giannakeas, I. N., Sharif Khodaei, Z., & Aliabadi, M. H. F., 2023. Sensitivity analysis of temperature effects on guided wave-based damage detection. Mechanical Systems and Signal Processing, 196, 110322. Ricci, F., Monaco, E., Boffa, N. D., Maio, L., Memmolo, V., 2022. Guided waves for structural health monitoring in composites: A review and implementation strategies. Progress in Aerospace Sciences, 129, 100790. Toh, G., Park, J., 2020., Review of vibration-based structural health monitoring using deep learning. Applied Sciences, 10(5),1680. Yue, N., Aliabadi, M. H., 2020. A scalable data-driven approach to temperature baseline reconstruction for guided wave structural health monitoring of anisotropic carbon-fibre-reinforced polymer structures. Structural Health Monitoring, 19(5), 1487 – 1506. Yue, N., Khodaei, Z. S., & Aliabadi, M. H., 2021. Damage detection in large composite stiffened panels based on a novel SHM building block philosophy. Smart Materials and Structure s , 30(4), 045004. Zhang, Z., He, M., Liu, A., Singh, H. K., Ramakrishnan, K. R., Hui, D., 2018. Vibration-based assessment of delaminations in FRP composite plates. Composites Part B: Engineering, 144, 254 – 266.