مجله علمی صوت و ارتعاش

مجله علمی صوت و ارتعاش

مرور و مقایسه روش‌های ردیابی آسیب در سازه‌ها با استفاده از پارامترهای مودال

نوع مقاله : مقاله ترویجی

نویسنده
شرکت نفت مناطق مرکزی ایران
چکیده
پایش وضعیت سازه‌ها به منظور تشخیص آسیب یا هر عاملی که سبب خارج شدن از محدوده ایمن بهره‌برداری گردد، حائز اهمیت است. تحلیل رفتار و ویژگی‌های ارتعاشی سازه‌ها، یکی از روش‌های کم هزینه و قابل اجرا در مقیاس بزرگ برای پایش وضعیت سازه‌ها می‌باشد. وقوع آسیب سبب ایجاد تغییراتی در پارامترهای مودال سازه نظیر فرکانس‌های طبیعی و شکل مودها می‌شود که با بررسی آن­ها می‌توان به اطلاعاتی در مورد وضعیت سازه دست یافت. در مقاله حاضر، تحقیقات انجام شده در حوزه پایش وضعیت با استفاده از پارامترهای مودال مرور شده و مزایا، معایب و محدودیت‌های استفاده از فرکانس‌های طبیعی و شکل مودها در ردیابی آسیب مشخص می‌شود. سعی شده که در قالب دو مثال روش‌های مختلف با هم مقایسه شوند. در ابتدا ردیابی آسیب در یک تیر اویلر- برنولی با چند روش تحلیل شکل مود انجام شده و کارایی آن­ها با هم مقایسه می‌شود. در ادامه روش‌های معکوس مبتنی بر پارامترهای مودال برای ردیابی آسیب در مدل گسسته یک ساختمان 5 طبقه مقایسه شده و بهترین ترکیب اطلاعات برای افزایش دقت ردیابی آسیب مشخص می‌گردد.


 


 

 
 
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Review and comparison of damage detection methods in structures using modal parameters

نویسنده English

Alborz Mirzabeigy
Iranian central oil field company
چکیده English

Monitoring the condition of structures is important to detect damage or any factor that causes them to go beyond the safe operating range. Analysis of the behavior and vibration characteristics of structures is one of the low-cost and large-scale methods for monitoring the condition of structures. The occurrence of damage causes changes in the modal parameters of the structure, such as natural frequencies and mode shapes, which can be used to obtain information about the condition of the structure. In this article, research conducted in the field of condition monitoring using modal parameters is reviewed and the advantages, disadvantages, and limitations of using natural frequencies and mode shapes in damage tracking are determined. An attempt is made to compare different methods in the form of two examples. First, damage detection in an Euler-Bernoulli beam is performed using several mode shape analysis methods and their efficiency is compared. Next, inverse methods based on modal parameters for damage detection in a discrete model of a 5-story building are compared and the best combination of information is determined to increase the accuracy of damage tracking.

کلیدواژه‌ها English

Condition monitoring
vibration
modal parameters
natural frequency
mode shape
[1] Fan, Wei, and Pizhong Qiao. "Vibration-based damage identification methods: a review and comparative study." Structural health monitoring 10, no. 1 (2011): 83-111.
[2] Cawley, Peter. "Structural health monitoring: Closing the gap between research and industrial deployment." Structural Health Monitoring 17, no. 5 (2018): 1225-1244.
[3] Carden, E. Peter, and Paul Fanning. "Vibration based condition monitoring: a review." Structural Health Monitoring 3, no. 4 (2004): 355-377.
[4] Rezvani, Kamal, Maia NMM, and Mohammad H. Sabour. "A comparison of some methods for structural damage detection." Scientia Iranica 25.3 (2018): 1312-1322.
[5] Meruane, V., and W. Heylen. "An hybrid real genetic algorithm to detect structural damage using modal properties." Mechanical Systems and Signal Processing 25, no. 5 (2011): 1559-1573.
[6] Das, Swagato, Purna Saha, and S. K. Patro. "Vibration-based damage detection techniques used for health monitoring of structures: a review." Journal of Civil Structural Health Monitoring 6 (2016): 477-507.
[7] Dessi, Daniele, and Gabriele Camerlengo. "Damage identification techniques via modal curvature analysis: Overview and comparison." Mechanical Systems and Signal Processing 52 (2015): 181-205.
[8] Hou, Rongrong, and Yong Xia. "Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019." Journal of Sound and Vibration 491 (2021): 115741.
[9] Gudmundson, Peter. "Eigenfrequency changes of structures due to cracks, notches or other geometrical changes." Journal of the Mechanics and Physics of Solids 30.5 (1982): 339-353.
[10] Liang, Robert Y., Jialou Hu, and Fred Choy. "Theoretical study of crack-induced eigenfrequency changes on beam structures." Journal of Engineering Mechanics 118.2 (1992): 384-396.
[11] Adams, Robert D., et al. "A vibration technique for non-destructively assessing the integrity of structures." Journal of Mechanical Engineering Science 20.2 (1978): 93-100.
[12] Messina, Arcangelo, E. J. Williams, and T. Contursi. "Structural damage detection by a sensitivity and statistical-based method." Journal of Sound and Vibration 216.5 (1998): 791-808.
[13] Liang, Robert Y., Fred K. Choy, and Jialou Hu. "Detection of cracks in beam structures using measurements of natural frequencies." Journal of the Franklin Institute 328.4 (1991): 505-518.
[14] Patil, D. P., and S. K. Maiti. "Detection of multiple cracks using frequency measurements." Engineering Fracture Mechanics 70.12 (2003): 1553-1572.
[15] Murigendrappa, S. M., S. K. Maiti, and H. R. Srirangarajan. "Experimental and theoretical study on crack detection in pipes filled with fluid." Journal of Sound and Vibration 270.4-5 (2004): 1013-1032.
[16] Salawu, Olusegun S. "Detection of structural damage through changes in frequency: a review." Engineering Structures 19.9 (1997): 718-723.
[17] Farrar, Charles Reed, and G. H. James Iii. "System identification from ambient vibration measurements on a bridge." Journal of Sound and Vibration 205.1 (1997): 1-18.
[18] Hu, Chuanshuang, and Muhammad T. Afzal. "A statistical algorithm for comparing mode shapes of vibration testing before and after damage in timbers." Journal of Wood Science 52 (2006): 348-352.
[19] Pawar, Prashant M., Kanchi Venkatesulu Reddy, and Ranjan Ganguli. "Damage detection in beams using spatial Fourier analysis and neural networks." Journal of Intelligent Material Systems and Structures 18.4 (2007): 347-359.
[20] Abdo, MA-B., and Muneo Hori. "A numerical study of structural damage detection using changes in the rotation of mode shapes." Journal of Sound and Vibration 251.2 (2002): 227-239.
[21] Pandey, A. K., M. Biswas, and M. M. Samman. "Damage detection from changes in curvature mode shapes." Journal of Sound and Vibration 145.2 (1991): 321-332.
[22] Wahab, MM Abdel, and Guido De Roeck. "Damage detection in bridges using modal curvatures: application to a real damage scenario." Journal of Sound and Vibration 226.2 (1999): 217-235.
[23] Amaravadi, Venkata Kasi, et al. "Structural health monitoring using wavelet transforms." Smart Structures and Materials 2001: Smart Structures and Integrated Systems. Vol. 4327. SPIE, 2001.
[24] Kim, Hansang, and Hani Melhem. "Damage detection of structures by wavelet analysis." Engineering structures 26.3 (2004): 347-362.
[25] رضایی­فر، ا.، قلهکی، م.، خان­احمدی، م. و امیری، یاسر.، "مروری بر پایش سلامت و تشخیص آسیب در سازه‌ها با استفاده از تبدیل موجک (با مطالعه موردی شناسایی آسیب در تیر طره)"، نشریه صوت و ارتعاش،  1401، شماره 21، دوره 11، صفحه 157-171.
[26] Lee, Eun-Taik, and Hee-Chang Eun. "Damage detection of steel beam using frequency response function measurement data and fractal dimension." Journal of Vibration and Acoustics 137.3 (2015): 034503.
[27] Hadjileontiadis, L. J., E. Douka, and A. Trochidis. "Fractal dimension analysis for crack identification in beam structures." Mechanical Systems and Signal Processing 19.3 (2005): 659-674.
[28] Katz, Michael J. "Fractals and the analysis of waveforms." Computers in biology and medicine 18.3 (1988): 145-156.
[29] Moradi, S., P. Razi, and L. Fatahi. "On the application of bees algorithm to the problem of crack detection of beam-type structures." Computers & Structures 89.23-24 (2011): 2169-2175.
[30] Nanda, Bharadwaj, Damodar Maity, and Dipak K. Maiti. "Crack assessment in frame structures using modal data and unified particle swarm optimization technique." Advances in Structural Engineering 17.5 (2014): 747-766.
[31] Pandey, A. K., and M. Biswas. "Damage detection in structures using changes in flexibility." Journal of sound and vibration 169.1 (1994): 3-17.
[32] Zhang, Z., and A. E. Aktan. "Application of modal flexibility and its derivatives in structural identification." Journal of Research in Nondestructive Evaluation 10.1 (1998): 43-61.
[33] Wu, D., and S. S. Law. "Damage localization in plate structures from uniform load surface curvature." Journal of Sound and Vibration 276.1-2 (2004): 227-244.
[34] Masoumi, M. A. S. O. U. D., and M. R. Ashory. "Damage identification from uniform load surface using continuous and stationary wavelet transforms." Latin American Journal of solids and structures 11 (2014): 738-754.
[35] Mirzabeigy, Alborz, and Reza Madoliat. "An inverse approach based on uniform load surface for damage detection in structures." Smart Structures and Systems 24.2 (2019): 233-242.
[36] Rahita, Aulia Chanief, et al. "Internet of Things (IoT) in Structural Health Monitoring: A Decade of Research Trends." Instrumentation, Mesures, Métrologies 23.2 (2024).
[37] Mishra, Mayank, Paulo B. Lourenço, and Gunturi Venkata Ramana. "Structural health monitoring of civil engineering structures by using the internet of things: A review." Journal of Building Engineering 48 (2022): 103954.
[38] Avci, Onur, et al. "A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications." Mechanical systems and signal processing 147 (2021): 107077.
[39] Malekloo, Arman, et al. "Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights." Structural Health Monitoring 21.4 (2022): 1906-1955.
[40] Danish, Aamar, Faran Tayyab, and Muhammad Usama Salim. "Health assessment based on dynamic characteristics of reinforced concrete beam using realtime wireless structural health monitoring sensor." Journal of Structural Integrity and Maintenance 5.3 (2020): 204-210.
[41] Muttillo, Mirco, et al. "Structural health monitoring: An IoT sensor system for structural damage indicator evaluation." Sensors 20.17 (2020): 4908.
[42] Huang, Minshui, et al. "Damage identification of steel bridge based on data augmentation and adaptive optimization neural network." Structural Health Monitoring 24.3 (2025): 1674-1699.
[43] Teng, Shuai, et al. "Vibration-based structural damage detection using 1-D convolutional neural network and transfer learning." Structural Health Monitoring 22.4 (2023): 2888-2909.
[44] Khatir, Abdelwahhab, et al. "A new hybrid PSO-YUKI for double cracks identification in CFRP cantilever beam." Composite Structures 311 (2023): 116803.
[45] Zhou, Wei, and Y. F. Xu. "Damage identification for plate structures using physics-informed neural networks." Mechanical Systems and Signal Processing 209 (2024): 111111.
[46] Khaji, N., and M. Mehrjoo. "Crack detection in a beam with an arbitrary number of transverse cracks using genetic algorithms." Journal of Mechanical Science and Technology 28.3 (2014): 823-836.
[47] Rao, R. Venkata, Vimal J. Savsani, and D. P. Vakharia. "Teaching–learning-based optimization: an optimization method for continuous non-linear large-scale problems." Information sciences 183.1 (2012): 1-15.
[48] Nguyen, Khoa Viet. "Crack detection of a double-beam carrying a concentrated mass." Mechanics Research Communications 75 (2016): 20-28.