تشخیص آسیب در سازه های فلزی با استفاده از اطلاعات خیز استاتیکی و الگوریتم ژنتیک

نویسندگان

1 دانشگاه صنعتی نوشیروانی بابل

2 دانشگاه علم و صنعت ایران

چکیده

تشخیص زود هنگام محل و شدت آسیب های رخداده در سازه ها با کمک روش های غیر مخرب از اهمیت ویژه ای برخوردار است. در این مقاله به تشخیص آسیب در سازه ها با استفاده از اطلاعات استاتیکی پرداخته شده است. مدل سازی آسیب، به صورت کاهش در پارامترهای سازه ای انجام شده است. ابتدا نیروهای استاتیکی به برخی درجات آزادی سازه اعمال شده و پاسخ استاتیکی همان درجات ثبت گردیده است. نهایتا، تابع هدفی بر اساس اختلاف بین بردارهای جابجایی در حالت سازه سالم و آسیب دیده تعریف شده است، بطوریکه جواب بهینه این تابع، مبین آسیب های بوجود آمده در سازه می باشد. برای حل مسئله ی بهینه یابی، از الگوریتم ژنتیک استفاده شده است. به منظور بررسی کارآیی روش ارائه شده، مدلی از پل قوسی فلزی و همچنین پل خرپایی در نظر گرفته شده و سناریو های آسیب مختلفی مورد مطالعه قرار گرفته است. نتایج به دست آمده نشان می دهد که الگوریتم ژنیتک با تابع هدف ارائه شده، قادر است تا با دقت قابل قبولی، حتی در حضور نوفه‌های تصادفی، مکان و مقدار آسیب های احتمالی را شناسایی کند.

کلیدواژه‌ها


عنوان مقاله [English]

Damage detection in steel structures using static data via Genetic Algorithm

نویسندگان [English]

  • Zahra Tabrizian 1
  • Morteza Hossein Ali Beigy 1
  • Gholamreza Ghodrati Amiri 2
1 babol university
2 university
چکیده [English]

Structural damage detection technique helps to locate and detect damage that occurred in a structure by using the observed changes of its dynamic and static characteristics. The existing approaches proposed in this area can be divided into two main groups: the dynamic damage detection methods using dynamic data and the static damage detection methods using static data (static displacement, static strain etc.). As the static equilibrium equation is only related to the structural stiffness, accurate static displacement and strain data, it can be obtained rapidly and cheaply. For the reasons stated, the static damage detection methods have attracted more attention in recent years This paper presents a non-destructive global structural damage detection and assessment algorithm using static data. A set of static forces is applied to a set of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. Some simultaneous equations characterized from Changes in the static response which structural damage caused. The method is determined damage as a change in the structural stiffness parameter. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the load vector of damaged and healthy structure. As mentioned above the static damage identification methods have many advantages, but some difficulties still exist. The main problems the first of all is, the information used in the static damage identification methods is less than in the dynamic identification, which makes it more difficult to get the ideal identification result. For example, the angular displacement or rotational freedom is difficult to determine. Second, the effects of the damage may be concealed due to the limited load paths. Lastly, the static data provide only the local structural damage information, and the measured static data are very limited. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. Damage defined by several scenarios included single scenario and multiple scenarios. For example in plane truss scenario two means: 40% damage in element No. 2 and 60% damage in element No. 10. Numerical results in this paper for a plane arch bridge and a plane truss show the ability of this method in detecting damage in given structures. Also Figures show damage detections in multiple damage scenarios have really nice answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

کلیدواژه‌ها [English]

  • structural damage detection
 
[1] Carden, E. P., and Fanning, P., (2004). Vibration based condition monitoring: a review. Struct. Health Monit. 3(4) 355–377.
[2]Fan, W., and Qiao, P., (2011). Vibration-based damage identification methods: a review and comparative study. Struct. Health Monit. 10(1) 83–111.
[3]Bagheri, A., Ghodrati Amiri, G., Khorasani, M., and Bakhshi, H. (2011). Structural damage identification of plates based on modal data using 2D discrete wavelet transform. Struct. Eng. Mech. 40(1) 13–28.
[4]W. Bayissa, N. Haritos, S. Thelandersson, (2008). Vibration-based structural damage identification using wavelet transform, Mechanical Systems and Signal Processing. 22(5) 1194–1215.
[5]Y.J. Yan, L.H. Yam, (2002). Online detection of crack damage in composite plates using embedded piezoelectric actuators/sensors and wavelet analysis, Composite Structures, 58(1) 29–38.
[6]Friswell, M. L, Penny, J. E. T., Garvey, S. D.A.(1998). Combined Genetic and Eigensensitivity Algorithm for the Location of Damage in Structures. Computers and Structures ,69 ,547-556
[7]Bernstein, S., Richter. M. "The Use of Genetic Algorithms in Finite Element Model Identification," Bauhaus-Universitat at Weimar, Mathematische Optimierung, Coudraystr. 13B, 99421 Weimar, Germany, 2003.
[8]G. Ghodrati Amiri, Seyed Razzaghi, S.A., Bagheri, A. 2011., Damage detection in plates based on pattern search and genetic algorithms. Smart Structures and Systems, 7(2)117-132.
[9]Tabrizian, Z., Afshari, E., Ghodrati A., Gh., H. A. Beigy, M., Pourhoseini N., S. M., (2013).A new damage detection method: Big Bang-Big Crunch (BB-BC) algorithm. Shock and Vibration;  20( 4) 633-648, .
[10]Sanayei, M., and Onipede, O., (1991). "Damage Assessment of Structures Using Static Test Data," AIAA Journal, 29(7)1174-1179.
[11]Sanayei, M., and Scampoli, S., (1991). "Structural Element Stiffness Identification from Static Test Data," ASCE, Journal of Engineering Mechanics, 117(5) 1021-1036.
[12]Sanayei, M., and Saletnik, M. J., (1996). "Parameter Estimation of Structures from Static Strain Measurements; II: Error Sensitivity Analysis," ASCE, Journal of Structural Engineering, 122(5) 563-572.
[13] Hjelmstad KD, Shin S, (1997). “Damage detection and assessment of structures from static response”, J Eng Mech, 123(6) 568–576.
[14] Maosen Cao, L.Y., Limin Zhou, Zhongqing Su, Runbo Bai  Sensitivity of fundamental mode shape and static deflection for damage identification in cantilever beams. Mechanical Systems and Signal Processing, 2011. 25: p. 13.
[15]Holland J.H., Adaptation in Natural and Artificial Systems, University of Michigan Press, Michigan. S., 1975.
[16]Goldberg, D.E.a.S., Manohar  P.  , Engineering optimization via genetic algorithm, in Ninth Conference on Electronic Computation,1986, ASCE: New York, N.Y., 471-478.