Identification of Structural Damage in Frame Bridge Using Mode Shape Curvature: Simulation on Laboratory-Scale Frame Bridge

Djoko Irawan, Budi Suswanto, Ahmad Basshofi Habieb, Dita Kamarul Fitriyah

Abstract


Most bridge construction is dominated by steel bridges with various designs and structural types. The choice of steel as a material is due to its known strength, durability, and resistance to damage. However, if maintenance activities on steel bridges are lacking, there is a potential for damage or even failure of the structure. Structural failure can result in economic losses for the country, and more importantly, it can pose a threat to human safety. Therefore, there is a need for monitoring activities to assess the structural health. The development of monitoring activities in the last decade includes the Structural Health Monitoring System (SHMS). To address the challenges of SHMS, various methods are being researched. Non-Destructive Testing (NDT) methods are considered the best choice as an inspection tool, being perceived as easy, and effective in detecting and diagnosing various structural issues. Hence, in research, the detection of damage locations in steel bridge structures is carried out using the Mode Shape Curvature (MSC) method with the assistance of an accelerometer sensor. The MSC method contributes to SHM at level II, specifically in detecting the location of damage in the structure. It is observed that in the designed damage scenarios, the MSC index indicates a loss of stiffness with an increase in the MSC value at the damage location.


Keywords


Damage Detection; MSC; NDT; SHM; Truss Bridge

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References


M. S. Wibawa, A. I. Ubay, S. A. Putra, and A. Syahrina, “Integrasi Sistem Pengawasan Kesehatan Jembatan dengan Sistem Pengawasan Lalu Lintas ( The Integration of Bridge Health Monitoring System with Traffic Monitoring System ),” no. May, 2020, doi: 10.22146/jnteti.v9i2.197.

A. Fatah, U. Ungkawa, M. M. Barmawi, J. T. Informatika, F. T. Industri, and F. Alami, “IMPLEMENTASI ALGORITMA FAST FOURIER TRANSFORM PADA MONITOR GETARAN UNTUK ANALISIS KESEHATAN,” vol. 5, no. 2, pp. 48–57, 2020, doi: 10.32897/infotronik.2020.5.2.414.

K. Chang and C. Kim, “Modal-parameter identification and vibration-based damage detection of a damaged steel truss bridge,” Eng. Struct., vol. 122, pp. 156–173, 2016, doi: 10.1016/j.engstruct.2016.04.057.

Purnomo, W. A. N. Aspar, W. Barasa, S. M. Harjono, P. Sukamdo, and T. Fiantika, “Initial Implementation of Structural Health Monitoring System of a Railway Bridge,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1200, no. 1, p. 012019, 2021, doi: 10.1088/1757-899x/1200/1/012019.

C. Comisu, N. Taranu, G. Boaca, and M. Scutaru, “ScienceDirect ScienceDirect ScienceDirect Structural health health monitoring monitoring system system of of bridges bridges Structural,” Procedia Eng., vol. 199, pp. 2054–2059, 2017, doi: 10.1016/j.proeng.2017.09.472.

S. Saman, K. Dolati, N. Caluk, A. Mehrabi, S. Sasan, and K. Dolati, “applied sciences Non-Destructive Testing Applications for Steel Bridges,” pp. 1–34, 2021.

S. Lee and N. Kalos, “Bridge inspection practices using non-destructive testing methods,” J. Civ. Eng. Manag., vol. 21, no. 5, pp. 654–665, 2015, doi: 10.3846/13923730.2014.890665.

Y. J. Yan, L. Cheng, Z. Y. Wu, and L. H. Yam, “Development in vibration-based structural damage detection technique,” Mech. Syst. Signal Process., vol. 21, no. 5, pp. 2198–2211, 2007, doi: 10.1016/j.ymssp.2006.10.002.

L. Bernardini and M. Carnevale, “applied sciences Damage Identification in Warren Truss Bridges by Two Different Time – Frequency Algorithms,” 2021.

X. Lei, L. Sun, Y. Xia, and T. He, “Vibration-based seismic damage states evaluation for regional concrete beam bridges using random forest method,” Sustain., vol. 12, no. 12, 2020, doi: 10.3390/su12125106.

W. Fan and P. Qiao, “Vibration-based Damage Identification Methods : A Review and Comparative Study,” vol. 10, no. 1, pp. 83–111, 2016.

F. Omar et al., “Global methodology for damage detection and localization in civil engineering structures,” Eng. Struct., vol. 171, pp. 686–695, 2018, doi: 10.1016/j.engstruct.2018.06.026.

S. Rucevskis and M. Wesolowski, “Identification of damage in a beam structure by using mode shape curvature squares,” Shock Vib., vol. 17, no. 4–5, pp. 601–610, 2010, doi: 10.3233/SAV-2010-0551.

O. Avci, O. Abdeljaber, S. Kiranyaz, M. Hussein, M. Gabbouj, and D. J. Inman, “A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications,” Mech. Syst. Signal Process., vol. 147, 2021, doi: 10.1016/j.ymssp.2020.107077.

E. Manoach, J. Warminski, L. Kloda, and A. Teter, “Vibration Based Methods For Damage Detection In Structures,” MATEC Web Conf., vol. 83, no. April 2018, 2016, doi: 10.1051/matecconf/20168305007.

E. Wahyuni, “Studi Kelakuan Dinamis Struktur Jembatan Penyeberangan Orang ( JPO ) Akibat Beban Individual Manusia Bergerak,” vol. 19, no. 3, pp. 181–194, 2012.




DOI: https://doi.org/10.31284/j.iptek.2024.v28i1.5291

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