Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/161342
Title: Bayesian dynamic programming approach for tracking time-varying model properties in SHM
Authors: Yang, Yanping
Zhu, Zuo
Au, Siu-Kui
Keywords: Engineering::Civil engineering
Issue Date: 2023
Source: Yang, Y., Zhu, Z. & Au, S. (2023). Bayesian dynamic programming approach for tracking time-varying model properties in SHM. Mechanical Systems and Signal Processing, 185, 109735-. https://dx.doi.org/10.1016/j.ymssp.2022.109735
Project: SUG/4 (04INS000618C120)
RG68/22
Journal: Mechanical Systems and Signal Processing 
Abstract: Structural health monitoring (SHM) quite often involves continually tracking the temporal variation of some properties of interest, where statistical information about variations under normal situation can be obtained and potential anomalies may be detected for further attention. Structural-related properties such as natural frequency and stiffness often need to be identified with a physics-based model that relates them to measured data. Conventional approaches empirically divide data into non-overlapping segments with equal lengths and identify the model parameters within each segment based on a time-invariant model. Potentially time-varying model properties are then investigated based on the variation of identified results from one data segment to another. Challenges do exist, e.g., how to choose segment length to balance modeling error and identification accuracy, how to set criterion for anomaly detection, etc., which should be addressed with proper extraction of probabilistic information from data. In this work, the SHM problem is formulated as a Bayesian model selection problem, where the data can be ‘partitioned’ in an arbitrary manner, whose optimal choice, and hence points of significant change, are determined together with the model inference process by maximizing the probabilistic evidence supported by data. An efficient algorithm based on dynamic programming is proposed to determine the optimal partitioning and associated piecewise-constant properties, which is otherwise computationally prohibitive. The methodology is applied to tracking modal properties, e.g., natural frequency and damping ratio, of structures using output-only ambient vibration data. It is investigated with synthetic data and then applied to field data of a tall building during a typhoon event.
URI: https://hdl.handle.net/10356/161342
ISSN: 0888-3270
DOI: 10.1016/j.ymssp.2022.109735
Rights: © 2022 Elsevier Ltd. All rights reserved. This paper was published in Mechanical Systems and Signal Processing and is made available with permission of Elsevier Ltd.
Fulltext Permission: embargo_20250215
Fulltext Availability: With Fulltext
Appears in Collections:CEE Journal Articles

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