Dr. Yong Huang Profile

Dr. Yong Huang

at Harbin Institute of Technology

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Publications (7)

Proceedings Article | 12 April 2017 Paper

Prediction-error variance in Bayesian model updating: a comparative study

Parisa Asadollahi, Jian Li, Yong Huang

Proceedings Volume 10168, 101683P (2017) https://doi.org/10.1117/12.2260398

KEYWORDS: Monte Carlo methods, Probability theory, Performance modeling, Stochastic processes, Error analysis, Buildings, Statistical modeling, Shape analysis, Mathematical modeling, Process modeling, Statistical analysis, Systems modeling

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In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes’ Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model class level produces more robust results especially when the number of measurement is small.

Proceedings Article | 20 April 2012 Paper

Output only earthquake damage detection of moment resist frame using wavelet analysis and fractal dimension

Dongwang Tao, Hui Li, Yong Huang, Yuequan Bao

Proceedings Volume 8348, 834820 (2012) https://doi.org/10.1117/12.915008

KEYWORDS: Fractal analysis, Damage detection, Wavelets, Earthquakes, Wavelet transforms, Complex systems, Numerical simulations, Mathematical modeling, Optical simulations, Time-frequency analysis

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Proceedings Article | 20 April 2012 Paper

Stochastic optimization using automatic relevance determination prior model for Bayesian compressive sensing

Yong Huang, James Beck, Stephen Wu, Hui Li

Proceedings Volume 8348, 834837 (2012) https://doi.org/10.1117/12.921257

KEYWORDS: Reconstruction algorithms, Wavelets, Optimization (mathematics), Structural health monitoring, Stochastic processes, Compressed sensing, Data compression, Sensors, Data acquisition, Bridges

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Proceedings Article | 15 April 2011 Paper

Robust diagnostics for Bayesian compressive sensing with applications to structural health monitoring

Yong Huang, James Beck, Hui Li, Stephen Wu

Proceedings Volume 7982, 79820J (2011) https://doi.org/10.1117/12.880687

KEYWORDS: Diagnostics, Compressed sensing, Structural health monitoring, Data storage, Signal processing, Signal detection, Data compression, Interference (communication), Optimization (mathematics), Sensor networks

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Proceedings Article | 9 April 2010 Paper

Fractal theory and wavelet packet transform based damage detection method for beam structures

Yong Huang, Yongchao Yang, Hui Li

Proceedings Volume 7650, 76503I (2010) https://doi.org/10.1117/12.847825

KEYWORDS: Fractal analysis, Damage detection, Wavelets, Signal detection, Signal to noise ratio, Interference (communication), Time-frequency analysis, Sensors, Civil engineering, Structural health monitoring

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Proceedings Article | 9 April 2010 Paper

Structural damage detection based on non-negative matrix factorization and relevance vector machine

Yuequan Bao, Hui Li, Yong Huang, Jinping Ou

Proceedings Volume 7650, 76503H (2010) https://doi.org/10.1117/12.847823

KEYWORDS: Wavelets, Damage detection, Image classification, Bridges, Finite element methods, Feature extraction, Wavelet packet decomposition, Fusion energy, Pattern recognition, Chemical elements

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Proceedings Article | 21 October 2009 Paper

Damage identification method based on fractal dimension and Shannon entropy

Yong Huang, Hui Li, Yongchao Yang

Proceedings Volume 7493, 74936J (2009) https://doi.org/10.1117/12.838726

KEYWORDS: Fractal analysis, Image information entropy, Sensors, Optical simulations, Signal processing, Computer simulations, Beam shaping, Damage detection, Finite element methods, Signal to noise ratio

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Showing 5 of 7 publications

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