پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 653 |
| تعداد مقالات | 9,524 |
| تعداد مشاهده مقاله | 68,449,791 |
| تعداد دریافت فایل اصل مقاله | 47,909,603 |
Structural Damage Identification through an Optimal Sensor Placement Approach and the Modal Strain Energy Based Index | ||
| Journal of Rehabilitation in Civil Engineering | ||
| مقاله 9، دوره 12، شماره 1 - شماره پیاپی 33، اردیبهشت 2024، صفحه 127-144 اصل مقاله (1.57 M) | ||
| نوع مقاله: Regular Paper | ||
| شناسه دیجیتال (DOI): 10.22075/jrce.2023.29823.1805 | ||
| نویسندگان | ||
| Seyed Mohammad Seyedpoor* 1؛ Reza Yahyapour2؛ Ali Asghar Mofdi2؛ Saeed Fallahian3 | ||
| 1Associate Professor of Structural Engineering, Shomal University, Amol, Mazandaran, Iran | ||
| 2M.Sc. Graduated, Department of Civil Engineering, Shomal University, Amol, Mazandaran, Iran | ||
| 3Assistant Professor of Structural Engineering, Shomal University, Amol, Mazandaran, Iran | ||
| تاریخ دریافت: 15 بهمن 1401، تاریخ بازنگری: 22 اردیبهشت 1402، تاریخ پذیرش: 14 تیر 1402 | ||
| چکیده | ||
| In this study, an efficient method for determining the accurate location of damage to structures is introduced using an optimal sensor placement (OSP) and modal strain energy-based index (MSEBI). The research is implemented in two main stages. In the first stage, a correlation function between the reconstructed mode shapes using the iterated improved reduced system (IRS) method and the complete mode shapes of a structure is defined and then the function is minimized via the binary differential evolution (BDE) algorithm to find the optimal sensor placement of the structure. In the second stage, the location of damage is determined using MSEBI based on the optimum place of sensors obtained already. In order to assess the efficiency of the proposed method, two standard examples, including a two-dimensional (2-D) frame structure with 45 elements and a 2-D truss with 47 elements, are examined. Numerical results, considering different conditions, demonstrate that the integration of OSP method and MSEBI can provide an efficient tool for accurate and rapid identification of the damage location. The parametric study shows that the proposed method has a low sensitivity to the number of modes and noise level, and it can properly identify damage by considering a few modes and the high level of noise. | ||
| کلیدواژه‌ها | ||
| Damage identification؛ Optimal sensor placement؛ Modal strain energy؛ Iterated improved reduced system | ||
| مراجع | ||
|
[1] Nouri Y, Shariatmadar H, Shahabian F. Nonlinearity detection using new signal analysis methods for global health monitoring. Sci Iran 2023;30:845–59. https://doi.org/10.24200/sci.2022.58196.5610.
[2] Nouri Y, Shahabian F, Shariatmadar H, Entezami A. Structural Damage Detection in the Wooden Bridge Using the Fourier Decomposition, Time Series Modeling and Machine Learning Methods. J Soft Comput Civ Eng 2024;8:83–101. https://doi.org/10.22115/SCCE.2023.401971.1669.
[3] Fakharian P, Naderpour H. Damage Severity Quantification Using Wavelet Packet Transform and Peak Picking Method. Pract Period Struct Des Constr 2022;27:1–11. https://doi.org/10.1061/(asce)sc.1943-5576.0000639.
[4] Cha Y, Buyukozturk O. Structural Damage Detection Using Modal Strain Energy and Hybrid Multiobjective Optimization. Comput Civ Infrastruct Eng 2015;30:347–58. https://doi.org/10.1111/mice.12122.
[5] Pal J, Banerjee S. A combined modal strain energy and particle swarm optimization for health monitoring of structures. J Civ Struct Heal Monit 2015;5:353–63. https://doi.org/10.1007/s13349-015-0106-y.
[6] Khatir S, Abdel Wahab M, Boutchicha D, Khatir T. Structural health monitoring using modal strain energy damage indicator coupled with teaching-learning-based optimization algorithm and isogoemetric analysis. J Sound Vib 2019;448:230–46. https://doi.org/10.1016/j.jsv.2019.02.017.
[7] Teng S, Chen G, Liu G, Lv J, Cui F. Modal Strain Energy-Based Structural Damage Detection Using Convolutional Neural Networks. Appl Sci 2019;9:3376. https://doi.org/10.3390/app9163376.
[8] Wei ZT, Liu JK, Lu ZR. Damage identification in plates based on the ratio of modal strain energy change and sensitivity analysis. Inverse Probl Sci Eng 2016;24:265–83. https://doi.org/10.1080/17415977.2015.1017489.
[9] Wang X, Shi Q, Wang L, Lv Z, Chen X, Ma Y. Anisotropic reduction factor-based damage identification method for fiber-reinforced composite laminates. Struct Control Heal Monit 2018;25:e2253. https://doi.org/10.1002/stc.2253.
[10] Lale Arefi SH, Gholizad A, Seyedpoor SM. Damage detection of structures using modal strain energy with guyan reduction method. J Rehabil Civ Eng 2020;8:47–60. https://doi.org/10.22075/JRCE.2020.19803.1384.
[11] Seyedpoor SM. A two stage method for structural damage detection using a modal strain energy based index and particle swarm optimization. Int J Non Linear Mech 2012;47:1–8. https://doi.org/10.1016/j.ijnonlinmec.2011.07.011.
[12] Nobahari M, Seyedpoor SM. An efficient method for structural damage localization based on the concepts of flexibility matrix and strain energy of a structure. Struct Eng Mech 2013;46:231–44. https://doi.org/10.12989/sem.2013.46.2.231.
[13] Seyedpoor SM, Yazdanpanah O. An efficient indicator for structural damage localization using the change of strain energy based on static noisy data. Appl Math Model 2014;38:2661–72. https://doi.org/10.1016/j.apm.2013.10.072.
[14] Zepeng Chen, Yu L. A novel two-step intelligent algorithm for damage detection of beam-like structures. 2015 11th Int. Conf. Nat. Comput., IEEE; 2015, p. 633–8. https://doi.org/10.1109/ICNC.2015.7378063.
[15] Sun H, Büyüköztürk O. Optimal sensor placement in structural health monitoring using discrete optimization. Smart Mater Struct 2015;24:125034. https://doi.org/10.1088/0964-1726/24/12/125034.
[16] Zare Hosseinzadeh A, Ghodrati Amiri G, Seyed Razzaghi SA, Koo KY, Sung SH. Structural damage detection using sparse sensors installation by optimization procedure based on the modal flexibility matrix. J Sound Vib 2016;381:65–82. https://doi.org/10.1016/j.jsv.2016.06.037.
[17] Dinh-Cong D, Dang-Trung H, Nguyen-Thoi T. An efficient approach for optimal sensor placement and damage identification in laminated composite structures. Adv Eng Softw 2018;119:48–59. https://doi.org/10.1016/j.advengsoft.2018.02.005.
[18] Dinh-Cong D, Vo-Duy T, Nguyen-Thoi T. Damage assessment in truss structures with limited sensors using a two-stage method and model reduction. Appl Soft Comput 2018;66:264–77. https://doi.org/10.1016/j.asoc.2018.02.028.
[19] Yang C, Liang K, Zhang X, Geng X. Sensor placement algorithm for structural health monitoring with redundancy elimination model based on sub-clustering strategy. Mech Syst Signal Process 2019;124:369–87. https://doi.org/10.1016/j.ymssp.2019.01.057.
[20] Zargarzadeh A, Mojtahedi A, Mohammadyzadeh S, Hokmabady H. Employing an improved cross model cross mode algorithm for damage detection of a steel offshore platform frame using experimental data. Structures 2020;28:1589–600. https://doi.org/10.1016/j.istruc.2020.09.072.
[21] Yang C, Liang K, Zhang X. Strategy for sensor number determination and placement optimization with incomplete information based on interval possibility model and clustering avoidance distribution index. Comput Methods Appl Mech Eng 2020;366:113042. https://doi.org/10.1016/j.cma.2020.113042.
[22] Shi Q, Wang X, Chen W, Hu K. Optimal Sensor Placement Method Considering the Importance of Structural Performance Degradation for the Allowable Loadings for Damage Identification. Appl Math Model 2020;86:384–403. https://doi.org/10.1016/j.apm.2020.05.021.
[23] Yang C. An adaptive sensor placement algorithm for structural health monitoring based on multi-objective iterative optimization using weight factor updating. Mech Syst Signal Process 2021;151:107363. https://doi.org/10.1016/j.ymssp.2020.107363.
[24] GUYAN RJ. Reduction of stiffness and mass matrices. AIAA J 1965;3:380–380. https://doi.org/10.2514/3.2874.
[25] Friswell MI, Garvey SD, Penny JET. Model reduction using dynamic and iterated IRS techniques. J Sound Vib 1995;186:311–23. https://doi.org/10.1006/jsvi.1995.0451.
[26] Seyedpoor SM, Shahbandeh S, Yazdanpanah O. An efficient method for structural damage detection using a differential evolution algorithm-based optimisation approach. Civ Eng Environ Syst 2015;32:230–50. https://doi.org/10.1080/10286608.2015.1046051.
[27] Engelbrecht AP, Pampara G. Binary differential evolution strategies. 2007 IEEE Congr. Evol. Comput., IEEE; 2007, p. 1942–7. https://doi.org/10.1109/CEC.2007.4424711.
[28] Seyedpoor SM, Ahmadi A, Pahnabi N. Structural damage detection using time domain responses and an optimization method. Inverse Probl Sci Eng 2019;27:669–88. https://doi.org/10.1080/17415977.2018.1505884.
[29] Seyedpoor SM, Montazer M. A two-stage damage detection method for truss structures using a modal residual vector based indicator and differential evolution algorithm. Smart Struct Syst 2016;17:347–61. https://doi.org/10.12989/sss.2016.17.2.347. | ||
|
آمار تعداد مشاهده مقاله: 508 تعداد دریافت فایل اصل مقاله: 118 |
||