A Rapid Post-earthquake Structural Damage Identification Method Based on Mode Shape Ratio Using Pattern Matching
Journal: Journal of Building Technology DOI: 10.32629/jbt.v4i1.728
Abstract
This paper proposes a rapid identification method for post-earthquake structural damage based on mode shape ratio using pattern matching. In the first stage, the characteristic vector of mode shape ratio is calculated by modal analysis from the modal information of various damage scenarios to establish a pattern database. A small number of dynamic signals are collected for extracting the modal information to obtain the characteristic vector which is treated as the test pattern. Then the similarity between the test pattern and the pattern in the database is calculated using the Euclidean distance (ED). The damage location and severity of the measured structure are treated the same as the pattern corresponding to the minimum value of ED so that the damage is identified. Numerical simulations verify that the proposed method can well identify the damage. In addition, the matching results based on different sensor combinations demonstrate that the method can quickly identify the damage even using a limited number of sensors. The proposed method can provide support for the government to make a rapid post-earthquake emergency decision
Keywords
pattern matching; mode shape ratio; Euclidean distance; damage identification
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[2] Chatterjee A. (2010). Structural Damage Assessment in a Cantilever Beam with a Breathing Crack Using Higher Order Frequency Response Functions. Journal of Sound and Vibration, 329(16): 3325–3334.
[3] Caicedo J.M., Dyke S.J., Johnson E.A. (2004). Natural Excitation Technique and Eigensystem Realization Algorithm for Phase I of the IASC-ASCE Benchmark Problem: Simulated Data. Journal of Engineering Mechanics, 130(1): 49–60.
[4] Sun Z., Chang C.C. (2002). Structural Damage Assessment Based on Wavelet Packet Transform. Journal of Structural Engineering, 128(10): 1354–1361.
[5] Qiao L., Esmaeily A., Melhem H.G. (2008). Structural Damage Detection Using Signal Pattern-recognition. Key Engineering Materials, 400-402: 465–470.
[6] Lynch J.P., Wang Y., Lu K.C., et al. (2006). Post-seismic Damage Assessment of Steel Structures Instrumented with Self-interrogating Wireless Sensors. Proceedings of the 8th National Conference on Earthquake Engineering, 18.
[7] Yang X.F., Xiao L.F., Liu F.Y. (2015). Metal Structure Damage Location Pattern Matching Method Based on Virtual Damage Characteristics. 12th IEEE International Conference on Electronic Measurement & Instruments (ICEMI).
[8] Zhang M., Jin Y. (2008). Building Damage in Dujiangyan during Wenchuan Earthquake. Earthquake Engineering and Engineering Vibration, 7(3): 263–269.
[9] Rahutomo F., Kitasuka T., Aritsugi M. (2012). Semantic Cosine Similarity. The 7th International Student Conference on Advanced Science and Technology ICAST, 4(1): 1.
[10] Wang L., Zhang Y., Feng J. (2005). On the Euclidean Distance of Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8): 1334-1339.
[11] Wei G., Wang J., Lu M., et.al. (2019). Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their Applications. IEEE Access, 7: 159069–159080.
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