Neural Network Approach to Detection of Changes in Structural Parameters

Masri, Sami F.; Nakamura, Masatoshi; Chassiakos, Anastasios; Caughey, T. K.

doi:10.1061/(asce)0733-9399(1996)122:4(350)

Cited by 141 publications

(61 citation statements)

References 25 publications

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“…[30][31][32][33][34][35][36][37][38][39]). Masri et al [32,33] present a backpropagation neural network (BPNN)-based non-linear system identification approach for damage detection of unknown structural systems. First, vibration measurements from a healthy structure behaving elastically are used to train the BPNN model.…”

Section: Introductionmentioning

confidence: 98%

Pseudospectra, MUSIC, and dynamic wavelet neural network for damage detection of highrise buildings

Jiang

Adeli

2007

Numerical Meth Engineering

227

158

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SUMMARYA non-parametric system identification-based model is presented for damage detection of highrise building structures subjected to seismic excitations using the dynamic fuzzy wavelet neural network (WNN) model developed by the authors. The model does not require complete measurements of the dynamic responses of the whole structure. A large structure is divided into a series of sub-structures around a few pre-selected floors where sensors are placed and measurements are made. The new model balances the global and local influences of the training data and incorporates the imprecision existing in the sensor data effectively, thus resulting in fast training convergence and high accuracy. A new damage evaluation method is proposed based on a power density spectrum method, called pseudospectrum. The multiple signal classification (MUSIC) method is employed to compute the pseudospectrum from the structural response time series. The methodology is validated using the data obtained for a 38-storey concrete test model. The results demonstrate the effectiveness of the WNN model together with the pseudospectrum method for damage detection of highrise buildings based on a small amount of sensed data.

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Section: Introductionmentioning

confidence: 98%

Pseudospectra, MUSIC, and dynamic wavelet neural network for damage detection of highrise buildings

Jiang

Adeli

2007

Numerical Meth Engineering

227

158

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“…The direct use of time response in a model-based identification was proposed by [150,151] that used a least-squares sensitivity-based iterative parameter estimation routine. Masri et al [152] proposed a neural network based detection scheme that uses time responses both in the training and detection phases. Bu et al [153] and Lu and Liu [154] studied the direct use of time histories of vehicle or bridge acceleration in sensitivity-based model updating method.…”

Section: Objective Features and Functionsmentioning

confidence: 99%

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

2017

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Abstract:Research on detecting structural damage at the earliest possible stage has been an interesting topic for decades. Among them, the vibration-based damage detection method as a global technique is especially pervasive. The present study reviewed the state-of-the-art on the framework of vibration-based damage identification in different levels including the prediction of the remaining useful life of structures and the decision making for proper actions. This framework consists of several major parts including the detection of damage occurrence using response-based methods, building reasonable structural models, selecting damage parameters and constructing objective functions with sensitivity analysis, adopting optimization techniques to solve the problem, predicting the remaining useful life of structures, and making decisions for the next actions. For each part, the commonly used methods were reviewed and the merits and drawbacks were summarized to give recommendations. This framework is aimed to guide the researchers and engineers to implement step by step the structure damage identification using vibration measurements. Finally, the future research work in this field is recommended.

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“…Much research interest has been directed recently to system identification (SI) of civil, mechanical, and aerospace structures in response to the increasing need of enhancement of safety and upgrade of ability of damage detection (or damage diagnosis) of various kinds of structures (Hart and Yao, 1977;Beck and Jennings, 1980;Hoshiya and Saito, 1984;Kozin and Natke, 1986;Agbabian et al, 1991;Koh et al, 1991;Ghanem and Shinozuka, 1995;Hjelmstad et al, 1995;Shinozuka and Ghanem, 1995;Doebling et al, 1996;Hjelmstad, 1996;Masri et al, 1996;Housner et al, 1997;Kobori et al, 1998;Johnson and Smyth, 2006;Nagarajaiah and Basu, 2009;Fujino et al, 2010;Ji et al, 2011). Such need results from the accelerated demand of rapid assessment on material aging issues and of continuing use of buildings after earthquakes.…”

Section: Introductionmentioning

confidence: 99%

Application of Story-Wise Shear Building Identification Method to Actual Ambient Vibration

Fujita

Ikeda

Takewaki

2015

Front. Built Environ.

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Citation:Fujita K, Ikeda A and Takewaki I (2015) A sophisticated and smart story stiffness system identification (SI) method for a shear building model is applied to a full-scale building frame subjected to micro-tremors. The advantageous and novel feature is that not only the modal parameters, such as natural frequencies and damping ratios but also the physical model parameters, such as story stiffnesses and damping coefficients, can be identified using micro-tremors. While the building responses to earthquake ground motions are necessary in the previous SI method, it is shown in this paper that the micro-tremor measurements in a full-scale fivestory building frame can be used for identification within the same framework. The SI using micro-tremor measurements leads to the enhanced usability of the previously proposed story-wise shear building identification method. The degree of auto-regressive eXogenous models and the cut-off frequencies of band-pass filter are determined to derive reliable results.

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Neural Network Approach to Detection of Changes in Structural Parameters

Cited by 141 publications

References 25 publications

Pseudospectra, MUSIC, and dynamic wavelet neural network for damage detection of highrise buildings

Pseudospectra, MUSIC, and dynamic wavelet neural network for damage detection of highrise buildings

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

Application of Story-Wise Shear Building Identification Method to Actual Ambient Vibration

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