Damage Detection in Members and Connections of Plane Frame with Flexible Connections Using Residual Force Method and Whale Optimization Algorithm

Osman Hamdy1, Mahmoud T. Nawar2,3
1Department of Civil Engineering, Zagazig Higher Institute of Engineering & Technology, Zagazig, Egypt
2Engineering Management Department, College of Engineering, Prince Sultan University, Riyadh, Saudi Arabia
3Structural Engineering Department, Zagazig University, Zagazig, Egypt

Tóm tắt

This paper proposes a quantification and location damage detection model for plane frames with flexible connections considering simultaneous damage in members and connections. A two-phase method is produced to decrease the computational efforts considerably. The first phase presents proposed damage indicators depending on the residual force vector concept to obtain the expected damaged members and connections separately. The second phase considers damage quantification as a variable into the whale optimization algorithm (WOA) to obtain the optimum damage quantification value of the expected damaged members and connections attained in the first phase. WOA is a recent promising algorithm that has shown excellence in optimizing structural problems. Moreover, the biogeography-based optimization (BBO) is used in the second phase to compare the WOA and BBO algorithms. As it is obvious, the first phase diminishes the search space in the second phase, which in turn leads to a substantial reduction in computational efforts. The model is applied on three plane frame examples with flexible beam-to-column connections considering different damage scenarios. Results have proved the proficiency of the proposed method to accurately detect the quantification and location of damage with minimal computational efforts, and the superiority of WOA in comparison to BBO.

Tài liệu tham khảo

Avci O, Abdeljaber O, Kiranyaz S, Hussein M, Gabbouj M, Inman DJ (2021) A review of vibration-based damage detection in civil structures: From traditional methods to machine learning and deep learning applications. Mech Syst Signal Process. https://doi.org/10.1016/j.ymssp.2020.107077 Azim MR, Zhang H, Gül M (2020) Damage detection of railway bridges using operational vibration data: Theory and experimental verifications. Struct Monit Maintenance. https://doi.org/10.12989/smm.2020.7.2.149 Bakhtiari-Nejad F, Rahai A, Esfandiari A (2005) A structural damage detection method using static noisy data. Eng Struct. https://doi.org/10.1016/j.engstruct.2005.04.019 Begambre O, Laier JE (2009) A hybrid Particle Swarm Optimization—Simplex algorithm (PSOS) for structural damage identification. Adv Eng Softw. https://doi.org/10.1016/j.advengsoft.2009.01.004 Chen JC, Garba JA (1988) On-orbit damage assessment for large space structures. AIAA J 10(2514/3):10019 Cuong-Le T, Nghia-Nguyen T, Khatir S, Trong-Nguyen P, Mirjalili S, Nguyen KD (2021) An efficient approach for damage identification based on improved machine learning using PSO-SVM. Eng Comp. https://doi.org/10.1007/s00366-021-01299-6 Daum W (2013) Guidelines for structural health monitoring. In Handbook of Technical Diagnostics. https://doi.org/10.1007/978-3-642-25850-3_27 Nguyen DH, Bui TT, Roeck GD, Wahab MA (2019) Damage detection in Ca-Non Bridge using transmissibility and artificial neural networks. Struct Eng Mech 71(2):175–183 Eurocode 3. (2003). Design of steel structure. Part 1–8, Design of joints, BS EN 1993-I-X:2003. Fallah N, Vaez SRH, Mohammadzadeh A (2018) Multi-damage identification of large-scale truss structures using a two-step approach. J Build Eng 19:494–505. https://doi.org/10.1016/j.jobe.2018.06.007 Hasan NK, Hazim MD, Nasim S (2010) System identification of steel framed structures with semi-rigid connections. Struct Eng Mech 34(3):351–366. https://doi.org/10.12989/SEM.2010.34.3.351 Homaei F, Shojaee S, Amiri GG (2014) A direct damage detection method using Multiple Damage Localization Index Based on Mode Shapes criterion. Struct Eng Mech. https://doi.org/10.12989/sem.2014.49.2.183 Hoseini Vaez SR, Fallah N (2018) Damage identification of a 2D frame structure using two-stage approach. J Mech Sci Technol 32(3):1125–1133. https://doi.org/10.1007/s12206-018-0215-8 Hsu TY, Liu CL (2018) Damage detection of a thin plate using pseudo local flexibility method. Earthquake Struct. https://doi.org/10.12989/eas.2018.15.5.463 Khatir S, Abdel Wahab M (2019) Fast simulations for solving fracture mechanics inverse problems using POD-RBF XIGA and Jaya algorithm. Eng Fract Mech 205:285–300. https://doi.org/10.1016/j.engfracmech.2018.09.032 Khatir S, Abdel Wahab M, Boutchicha D, Khatir T (2019a) Structural health monitoring using modal strain energy damage indicator coupled with teaching-learning-based optimization algorithm and isogoemetric analysis. J Sound Vib 448:230–246. https://doi.org/10.1016/j.jsv.2019.02.017 Khatir S, Tiachacht S, Thanh C-L, Bui TQ, Abdel Wahab M (2019b) Damage assessment in composite laminates using ANN-PSO-IGA and Cornwell indicator. Compos Struct 230:111509. https://doi.org/10.1016/j.compstruct.2019.111509 Khatir S, Boutchicha D, Le Thanh C, Tran-Ngoc H, Nguyen TN, Abdel-Wahab M (2020) Improved ANN technique combined with Jaya algorithm for crack identification in plates using XIGA and experimental analysis. Theoret Appl Fract Mech 107:102554. https://doi.org/10.1016/j.tafmec.2020.102554 Koh BH, Dyke SJ (2007) Structural health monitoring for flexible bridge structures using correlation and sensitivity of modal data. Comput Struct. https://doi.org/10.1016/j.compstruc.2006.09.005 Lee K, Jeong S, Sim SH, Shin DH (2022) Damage-detection approach for bridges with multi-vehicle loads using convolutional autoencoder. Sensors. https://doi.org/10.3390/s22051839 Mares C, Surace C (1996) An application of genetic algorithms to identify damage in elastic structures. J Sound Vib. https://doi.org/10.1006/jsvi.1996.0416 Mirjalili S, Mirjalili SM, Saremi S, Mirjalili S (2020) Whale optimization algorithm: Theory, literature review, and application in designing photonic crystal filters. In Studies in Computational Intelligence (Vol. 811). Springer, Cham. https://doi.org/10.1007/978-3-030-12127-3_13 Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67. https://doi.org/10.1016/j.advengsoft.2016.01.008 Narges F, Seyed RHV, Hossein F (2018). Damage identification in laminated composite plates using a new multi-step approach. Steel Compos Struct 29(1):139–149. https://doi.org/10.12989/scs.2018.29.1.139 Nobahari M, Seyedpoor SM (2011) Structural damage detection using an efficient correlation-based index and a modified genetic algorithm. Math Comput Model. https://doi.org/10.1016/j.mcm.2010.12.058 Razavi M, Hadidi A (2020). Assessment of sensitivity-based FE model updating technique for damage detection in large space structures. Struct Monit Maintenance. https://doi.org/10.12989/smm.2020.7.3.261 Seyedpoor SM, Nopour MH (2020) A two-step method for damage identification in moment frame connections using support vector machine and differential evolution algorithm. Appl Soft Comput J. https://doi.org/10.1016/j.asoc.2019.106008 Shyamala P, Mondal S, Chakraborty S (2018) Numerical and experimental investigation for damage detection in FRP composite plates using support vector machine algorithm. Struct Monit Maintenance. https://doi.org/10.12989/smm.2018.5.2.243 Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702–713. https://doi.org/10.1109/TEVC.2008.919004 Wang X, Hu N, Fukunaga H, Yao ZH (2001) Structural damage identification using static test data and changes in frequencies. Eng Struct. https://doi.org/10.1016/S0141-0296(00)00086-9 Xiang J, Liang M (2012) A two-step approach to multi-damage detection for plate structures. Eng Fract Mech. https://doi.org/10.1016/j.engfracmech.2012.04.028 Yu H, Zhu HP, Weng S, Gao F, Luo H, De Ai M (2018) Damage detection of subway tunnel lining through statistical pattern recognition. Struct Monit Maintenance. https://doi.org/10.12989/smm.2018.5.2.231 Zenzen R, Belaidi I, Khatir S, Abdel Wahab M (2018) A damage identification technique for beam-like and truss structures based on FRF and Bat Algorithm. Comptes Rendus Mécanique 346(12):1253–1266. https://doi.org/10.1016/j.crme.2018.09.003 Zenzen R, Khatir S, Belaidi I, Le Thanh C, Abdel Wahab M (2020) A modified transmissibility indicator and Artificial Neural Network for damage identification and quantification in laminated composite structures. Compos Struct 248:112497. https://doi.org/10.1016/j.compstruct.2020.112497