Enhancing structural health monitoring of bridge beams through spectral moment analysis

  • Thanh Quang Nguyen

    STASD Reseach Group, Ho Chi Minh City University of Transport, No.2, Vo Oanh, Ho Chi Minh city, Vietnam
  • Thuy Tien Nguyen

    STASD Reseach Group, Ho Chi Minh City University of Transport, No.2, Vo Oanh, Ho Chi Minh city, Vietnam
Email: thuy.nguyen@ut.edu.vn
Từ khóa: structural defects, bridge beams, power spectrum, spectral moment, monitoring, characteristic quantity, deflection, natural frequency, mode shape, complex load conditions.

Tóm tắt

Investigating the occurrence of defects in structures is currently a major issue of significant interest. In this paper, we present experimental research findings on the relationship between the moments of the power spectrum and the presence of damage in bridge beam structures. The study is based on analysing the random oscillation signal of the structure under the effect of random displacement loads. The results demonstrate that the value of the spectral moment is a sensitive feature to abnormal changes inside the structure. As a result, the output obtained from our study suggests using the spectral moment parameter as a new characteristic quantity for monitoring changes in bridge structures. Compared to traditional quantities like deflection, natural frequency, and mode shape, the value of the spectral moment can be more accurately determined. In the future, the spectral moment value can be extended to evaluate different types of structures under complex load conditions.

Tài liệu tham khảo

[1]. Y.D. Yasuda, F.A. Cappabianco, L.E. Martins, J.A. Gripp, Aircraft visual inspection: A systematic literature review, Computers in Industry, 141 (2022) 103695. https://doi.org/10.1016/j.compind.2022.103695
[2]. B.A. Graybeal, B.M. Phares, D.D. Rolander, M. Moore, G. Washer, Visual inspection of highway bridges, Journal of nondestructive evaluation, 21 (2002) 67-83. https://doi.org/10.1023/A:1022508121821
[3]. D. Agdas, J.A. Rice, J.R. Martinez, I.R. Lasa, Comparison of visual inspection and structural-health monitoring as bridge condition assessment methods, Journal of Performance of Constructed Facilities, 30 (2016) 04015049. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000802
[4]. V. Gattulli, L. Chiaramonte, Condition assessment by visual inspection for a bridge management system, Computer‐Aided Civil and Infrastructure Engineering, 20 (2005) 95-107. https://doi.org/10.1111/j.1467-8667.2005.00379.x
[5]. I. Abdel-Qader, O. Abudayyeh, M.E. Kelly, Analysis of edge-detection techniques for crack identification in bridges, Journal of Computing in Civil Engineering, 17 (2003) 255-63, https://doi.org/10.1061/(ASCE)0887-3801(2003)17:4(255)
[6]. L.E. Campbell, R.J. Connor, J.M. Whitehead, G.A. Washer, Human factors affecting visual inspection of fatigue cracking in steel bridges, Structure and Infrastructure Engineering, 17 (2021) 1447-58. https://doi.org/10.1080/15732479.2020.1813783
[7]. X. Zhao, S. Li, H. Su, L. Zhou, K. J. Loh, Image-based comprehensive maintenance and inspection method for bridges using deep learning, in InSmart Materials, Adaptive Structures and Intelligent Systems 2018, American Society of Mechanical Engineers., 2018.
[8]. T. Q. Nguyen, L. C. Vuong, C. M. Le, N. K. Ngo, H. N. Xuan, A data-driven approach based on wavelet analysis and deep learning for identification of multiple-cracked beam structures under moving load, Measurement, 162 (2020) 107862. https://doi.org/10.1016/j.measurement.2020.107862
[9]. T. Q. Nguyen, L. Q. Tran, H. N. Xuan, N. K. Ngo, A statistical approach for evaluating crack defects in structures under dynamic responses, Nondestructive Testing and Evaluation, 36 (2021) 113-144. https://doi.org/10.1080/10589759.2019.1699086
[10]. H.B. Nguyen, T.Q. Nguyen, Detecting and Evaluating Defects in Beams by Correlation Coefficients, Shock and Vibration, 2021 (2021) 6536249. https://doi.org/10.1155/2021/6536249
[11]. T. D. Nguyen, T. Q. Nguyen, T. N. Nhat, H. N. Xuan, N. K. Ngo, A novel approach based on viscoelastic parameters for bridge health monitoring: a case study of Saigon bridge in Ho Chi Minh City–Vietnam, Mechanical systems and signal processing, 141 (2020) 106728. https://doi.org/10.1016/j.ymssp.2020.106728
[12]. T. Q. Nguyen, T.T.D. Nguyen, H. N. Xuan, N. K. Ngo, A correlation coefficient approach for evaluation of stiffness degradation of beams under moving load, Cmc-Computers Materials & Continua, 61 (2019) 27-53. https://doi.org/10.32604/cmc.2019.07756
[13]. T. Q. Nguyen, A data-driven approach to structural health monitoring of bridge structures based on the discrete model and FFT-deep learning, Journal of Vibration Engineering & Technologies, 9 (2021) 1959-1981. https://doi.org/10.1007/s42417-021-00343-5
[14]. Y. Cao, J. Yim, Y. Zhao, M.L. Wang, Temperature effects on cable stayed bridge using health monitoring system: a case study, Structural Health Monitoring, 10 (2011) 523-37. https://doi.org/10.1177/14759217103889
[15]. W. Zhang, J. Gao, B. Shi, H. Cui, H. Zhu, Health monitoring of rehabilitated concrete bridges using distributed optical fiber sensing, Computer‐Aided Civil and Infrastructure Engineering, 21 (2006) 411-24. https://doi.org/10.1111/j.1467-8667.2006.00446.x
[16]. Q. Zhang, Y. Zhou, Investigation of the applicability of current bridge health monitoring technology, Structure and Infrastructure Engineering, 3 (2007) 159-68. https://doi.org/10.1080/15732470600590762

Tải xuống

Chưa có dữ liệu thống kê
Nhận bài
07/04/2023
Nhận bài sửa
04/05/2022
Chấp nhận đăng
04/05/2023
Xuất bản
15/05/2023
Chuyên mục
Công trình khoa học
Số lần xem tóm tắt
82
Số lần xem bài báo
56