A Baseline free approach to detect multiple damages in a beam type structure using response-only techniques


  • Quratulain Masud University of Engineering & Technology Lahore
  • Ummul Baneen University of Engineering & Technology Lahore


Structural health monitoring (SHM) is an important area that ensures the integrity and safety of all structures related to aviation, civil and mechanical engineering. Structural damage greatly affects the dynamic properties of a structure which, in turn, alters its measured dynamic response or vibrational characteristics. Hence, researchers have exploited this relation by devising damage detection techniques that are based on natural frequencies, mode shapes, mode shape curvatures, operational deflection shapes, operational curvature shapes etc. In most of these techniques, presence of damage is ensured with the change in the measured response. The measured response is typically in the form of Frequency Response Functions (FRFs) which requires the information of input data, usually the excitation force. In practice, it is difficult to measure the excitation force in operational areas and particularly, in randomly excited structures. So, in case of unknown excitations the response-only techniques are found useful, as they do not require input information and generate transmissibility functions (TFs) which contain information about damage. Furthermore, the majority of damage detection methods including the response-only techniques require the data of intact structures to distinguish the change due to damage, which in case of existing structures is impractical. To address this issue, smoothing techniques are applied on the available data to get presumed baseline information of undamaged structure.  In this paper, two response-only techniques namely Operational deflection shape (ODS) FRF and Random Decrement (RanDec) are presented along with a smoothing technique to make the damage detection process baseline-free. To implement this modified approach in a beam-type structure, different damage scenarios are considered. The results of both response-only techniques are compared with those from FRFs and it is shown that RanDec technique gives better results when the record length of response and sampling time was increased.

Author Biographies

Quratulain Masud, University of Engineering & Technology Lahore


Department of Mechatronics & Control Engineering 

UET Lahore

Ummul Baneen, University of Engineering & Technology Lahore

Assistant Professor

Department of Mechatronics & Control Engineering 

UET Lahore


[1] Sarah, J., Hejazi, F., Rashid, R. S., & Ostovar, N. (2019, November). A review of dynamic analysis in frequency domain for structural health monitoring. In IOP Conference Series: Earth and Environmental Science (Vol. 357, No. 1, p. 012007). IOP Publishing

[2] Avci, O., Abdeljaber, O., Kiranyaz, S., Hussein, M., Gabbouj, M., & Inman, D. J. (2020). A Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications. arXiv preprint arXiv:2004.04373.

[3] Sha, G., Radzieński, M., Cao, M., & Ostachowicz, W. (2019). A novel method for single and multiple damage detection in beams using relative natural frequency changes. Mechanical Systems and Signal Processing, 132, 335-352.

[4] Salawu, O. S. (1997). Detection of structural damage through changes in frequency: a review. Engineering structures, 19(9), 718-723.

[5] Dahak, M., Touat, N., & Kharoubi, M. (2019). Damage detection in beam through change in measured frequency and undamaged curvature mode shape. Inverse Problems in Science and Engineering, 27(1), 89-114.

[6] Dems, K., & Turant, J. (2011). Structural damage identification using frequency and modal changes. Bulletin of the Polish Academy of Sciences. Technical Sciences, 59(1), 27-32.

[7] Roy, K. (2017). Structural damage identification using mode shape slope and curvature. Journal of Engineering Mechanics, 143(9), 04017110.

[8] Saravanan, T. J., Gopalakrishnan, N., & Hari, B. K. (2019). Damage identification in structural elements through curvature mode shapes and nonlinear energy operator. 1, 1(1), 33.

[9] Wang, S., & Xu, M. (2019). Modal strain energy-based structural damage identification: a review and comparative study. Structural Engineering International, 29(2), 234-248.

[10] Khatir, S., Wahab, M. A., Boutchicha, D., & Khatir, T. (2019). Structural health monitoring using modal strain energy damage indicator coupled with teaching-learning-based optimization algorithm and isogoemetric analysis. Journal of Sound and Vibration, 448, 230-246.

[11] Wahalthantri, B. L., Thambiratnam, D. P., Chan, T. H. T., & Fawzia, S. (2012). An improved method to detect damage using modal strain energy based damage index. Advances in Structural
Engineering, 15(5), 727-742.

[12] Liu, X., Lieven, N. A. J., & Escamilla-Ambrosio, P. J. (2009). Frequency response function shape-based methods for structural damage localisation. Mechanical systems and signal processing, 23(4), 1243-1259.

[13] Niu, Z. (2020). Frequency response-based structural damage detection using Gibbs sampler. Journal of Sound and Vibration, 470, 115160.

[14] Esfandiari, A., Nabiyan, M. S., & Rofooei, F. R. (2020). Structural damage detection using principal component analysis of frequency response function data. Structural Control and Health Monitoring, e2550.

[15] Kumar, K. A., & Reddy, D. M. (2016, July). Application of frequency response curvature method for damage detection in beam and plate like structures. In IOP Conference Series: Materials Science and Engineering (Vol. 149, No. 1, p. 012160).

[16] Sohn, H. (2007). Effects of environmental and operational variability on structural health monitoring. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 365(1851), 539-560.

[17] Erazo, K., Sen, D., Nagarajaiah, S., & Sun, L. (2019). Vibration-based structural health monitoring under changing environmental conditions using Kalman filtering. Mechanical systems and signal processing, 117, 1-15.

[18] Panikkaveettil, H., Roy, K., & Ray-Chaudhuri, S. (2014). Damage Characterization in Frame Structures using Output-only Modal and Feature-based Techniques. IFAC Proceedings Volumes, 47(1), 973-980.

[19] Dackermann, U., Smith, W. A., Alamdari, M. M., Li, J., & Randall, R. B. (2019). Cepstrum-based damage identification in structures with progressive damage. Structural Health Monitoring, 18(1), 87-102.

[20] Kordestani, H., Xiang, Y. Q., & Ye, X. W. (2018). Output-only damage detection of steel beam using moving average filter. Shock and Vibration, 2018.

[21] Bayissa, W. L., Haritos, N., & Sofi, M. (2011). Comparative study of broadband damage localization methods applied to test data. Ocean engineering, 38(2-3), 329-340.

[22] Richardson, M. H. (1997). Is it a mode shape, or an operating deflection shape?. SV Sound and vibration, 31(1), 54-61.

[23] Lin, C. S., & Chiang, D. Y. (2012). A modified random decrement technique for modal identification from nonstationary ambient response data only. Journal of mechanical science and technology, 26(6), 1687-1696.

[24] Kordestani, H., Zhang, C., & Shadabfar, M. (2020). Beam damage detection under a moving load using random decrement technique and Savitzky–Golay Filter. Sensors, 20(1), 243.

[25] Huang, Z., Li, Y., Hua, X., Chen, Z., & Wen, Q. (2019). Automatic Identification of Bridge Vortex-Induced Vibration Using Random Decrement Method. Applied Sciences, 9(10), 2049.

[26] Yoon, M. K., Heider, D., Gillespie, J. W., Ratcliffe, C. P., & Crane, R. M. (2010). Local damage detection with the global fitting method using operating deflection shape data. Journal of Nondestructive Evaluation, 29(1), 25-37.

[27] Sampaio, R. P. C., Maia, N. M. M., & Silva, J. M. M. (1999). Damage detection using the frequency-response-function curvature method. Journal of sound and vibration, 226(5), 1029-1042.

[28] Sampaio, R. P. C., Maia, N. M. M., & Silva, J. M. M. (1999). Damage detection using the frequency-response-function curvature method. Journal of sound and vibration, 226(5), 1029-1042.






Mechanical Engineering, Automotive, Mechatronics, Textile, Industrial and Manufacturing Engineering