Kapalı Sistemlerde Temel Kanunlar Kullanılarak Hasar Tespit Metoduna Dayalı İvmeölçer Kütle Çalışması

Temel süreklilik ve enerji denklemlerine göre pek çok inşaat mühendisliği yapısı kütle konum değişimine elverişli olan kapalı sistem olarak değerlendirilebilir. Yoğun trafik saatleri göz önüne alındığında, araç kütlesinin köprü üzerindeki konumunun değişken olduğu, ancak toplam kütlenin sabit kaldığı varsayılabilir. Bu çalışmada, sabit kütle dağılımına sahip sistemler için geçerli olan bir hasar göstergesi kullanılarak kapalı sistemlerdeki hasarın başarıyla tahmin edilebileceğinin gösterilmesi amaçlanmıştır. Analitik çalışmada, 100 elemanlı 200 derecelik serbest sabit serbest kiriş incelenmiş ve hasar pozisyonunun tespit edilebileceği sayısal olarak doğrulanmış ve parametrenin geçerliliği deneysel bir çalışmada incelenmiştir. Kirişin serbest ucundaki parça hariç; Hasarlı elemanlar üzerinden hesaplanan hasar göstergesinin, hasarsız elemanlarda hesaplanan hasar göstergesinin 60 katı olduğu tespit edilmiştir. Kirişin serbest ucundaki elemanlarda; ivmeölçerin kütlesine bağlı olarak bu oranın 6 ile 40 arasında olduğu görülmüştür. Bu nedenle, ivmeölçer kütlesi ve hasar göstergesi için bir kıstas önerilmiştir.

Anahtar Kelimeler:

Sistem tanımlama, modal plan, hasar tespit, ivme ölçer kütlesi, yapı malzemesi

Accelerometer Mass Loading Study Based on a Damage Identification Method using Fundamental Laws in Closed Systems

Many civil engineering structures can be evaluated as closed systems in which additional mass spatial distribution can change within the system in terms of the fundamental continuity and energy equations. Considering the heavy hours of traffic, it can be assumed that the position of the vehicle mass on the bridge is variable, but the total mass remains constant. This study aims to show that the damage to the closed systems can be successfully estimated by using a damage indicator that is valid for systems with constant mass distribution. In the analytical study, a 100-element 200 degree of freedom fixed-free beam is investigated and the assessment of the damage position is verified numerically and the validity of the parameter is examined in an experimental study. Except for the piece at the free end of the beam; It has been determined that the damage indicator calculated on the damaged elements is 60 times larger than the damage indicator calculated at the undamaged elements. In the elements at the free end of the beam; it was observed that this ratio is between 6 and 40 depending on the mass of the accelerometer. Therefore, a criterion for accelerometer mass and damage indicator is proposed.

Keywords:

System identification, modal plot, damage detection, accelerometer mass loading, structural material,

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[1] Aktan, A.E., Farhey, D.N., Brown, D.L., Dalal, V., Helmicki, A.J., Hunt, V.J. and Shelley, S.J., “Condition assessment for bridge management”, J. Infrastruct. Syst., 2(3), 108-17, (1996) https://doi.org/10.1061/(ASCE)1076-0342(1996)2:3(108).
[2] Tufan, T., “An investigation of system identification and damage estimation using modal plots, count plots and a damage indicator”, Ph.D. Dissertation, Bogazici University, Istanbul, (2020).
[3] Reynders, E., “System identification methods for (operational) modal analysis: review and comparison”, Archives of Computational Methods in Engineering, 19(1), 51-124, (2012).
[4] Tufan, T., Akalp, S., “Modal plot—System identification and fault detection”, Structuctural Control and Health Monitoring, e2347, (2019).
[5] Vicario, F., Phan, M. Q., Betti, R., Longman, R. W., “Output‐only observer/Kalman filter identification (O3KID)”, Structural Control and Health Monitoring, 22(5), 847-872, (2015).
[6] Doebling, S.W., Farrar, C.R., Prime, M.B. and Shevitz, D.W., “Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review”, Research Report No. LA-13070-MS; Los Alamos National Lab, NM, United States, (1996).
[7] Medhi, M., Dandautiya, A., & Raheja, J. L., “Real-time video surveillance based structural health monitoring of civil structures using artificial neural network”, Journal of Nondestructive Evaluation, 38(3), 63, (2019).
[8] Eroğlu, Y., Seçkiner S. U., “Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization”, Journal of Energy Systems. 3(4), 139-147, (2019).
[9] Azimi, M., Eslamlou, A. D., & Pekcan, G. “Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review”, Sensors, 20(10), 2778, (2020).
[10] Yang, J.N., “Application of optimal control theory to civil engineering structures”, J. Eng. Mech. Div.ASCE, 101(6), 819-838, (1975).
[11] Ren, W.X. and Zong, Z.H., “Output-only modal parameter identification of civil engineering structures”, Structural Engineering and Mechanics, 17(3-4), 429-444, (2004). http://dx.doi.org/10.12989/sem.2004.17.3_4.429.
[12] Peeters B., “System identification and damage detection in civil engeneering”, Ph.D. Dissertation, Katholieke Universiteit Leuven, (2000).
[13] Tufan, T, Köten, H., “Accelerometer Mass Loading Study Based on a Damage Identification Method using Fundamental Laws in Closed Systems”, 8th Eur. Conf. Ren. Energy Sys. (2020).
[14] Donadon, M. V., Almeida, S. D., & De Faria, A. R., “Stiffening effects on the natural frequencies of laminated plates with piezoelectric actuators”, Composites Part B: Engineering, 33(5), 335-342, (2002).
[15] Yadav, A., & Singh, N. K., “Investigation for accelerometer mass effects on natural frequency of magnesium alloy simply supported beam”, Materials Today: Proceedings, (2020).
[16] Lehmann, T., “Some thermodynamical considerations on inelastic deformations including damage processes”, Acta mechanica 79, no. 1-2: 1-24, (1989).
[17] Brünig, M., “An Anisotropic Continuum damage Model: Theory and Numerical Analyses”, Latin American Journal of Solids and Structures 1, no. 2: 185-218, (2004).
[18] Rytter, A. “Vibrational based inspection of civil engineering structures”. Ph.D. Dissertation, Aalborg University, (1993).
[19] Fassois, S. D. and Sakellariou, J. S., “Statistical Time Series Methods for SHM”. In Encyclopedia of Structural Health Monitoring. (eds Boller, C., Chang, F. and Fujino, Y.), (2009). https://doi.org/10.1002/9780470061626.shm044.
[20] Ayres, J.W., Lalande, F., Chaudhry, Z. and Rogers, C.A., “Qualitative impedance-based health monitoring of civil infrastructures”, Smart Mater. Struct. 7(5), 599, (1998). https://doi.org/10.1088/0964-1726/7/5/004.
[21] Gkoktsi, K., & Giaralis, A. “A compressive MUSIC spectral approach for identification of closely-spaced structural natural frequencies and post-earthquake damage detection”, Probabilistic Engineering Mechanics, 60, 103030, (2020). https://doi.org/10.1016/j.probengmech.2020.103030
[22] Tran-Ngoc, H., Khatir, S., De Roeck, G., Bui-Tien, T., & Wahab, M. A. “An efficient artificial neural network for damage detection in bridges and beam-like structures by improving training parameters using cuckoo search algorithm”, Engineering Structures, 199, 109637, (2019). https://doi.org/10.1016/j.engstruct.2019.109637
[23] Cawley, P. and Adams R. D., “The location of defects in structures from measurements of natural frequencies”, The Journal of Strain Analysis for Engineering Design, 14(2), 49-57, (1979).
[24] Hearn, G. and Testa B. R., “Modal Analysis for Damage Detection in Structures”, J. Structural Engrg., 117-10, (1991).
[25] Pandey, A. K., Biswas M., Samman, M. M., “Damage detection from changes in curvature mode shapes”, Journal of sound and vibration, 145(2), 321-332, (1991).
[26] Yuen, M.M.F., “A Numerical Study of the Eigenparameters of a Damaged Cantilever”, J Sound Vib, 103, 301–310, (1985). https://doi.org/10.1016/0022-460X(85)90423-7.
[27] Dong, C., Zhang, P.Q., Feng, W.Q. and Huang, T.C. The sensitivity study of the modal parameters of a cracked beam. Proceedings of the 12th International Modal Analysis, Schenectady, New York, USA, January, (1994).