Dynamic Fuzzy Wavelet Neural Network Model for Structural System Identification

Adeli, Hojjat; Jiang, Xiang

doi:10.1061/(asce)0733-9445(2006)132:1(102)

Cited by 318 publications

(223 citation statements)

References 33 publications

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“…The general discrete dynamic input-output mapping in the dynamic fuzzy WNN approach is expressed as follows [41]:…”

Section: Dynamic Fuzzy Wnn Model For Damage Detectionmentioning

confidence: 99%

“…To the best of the authors' knowledge, however, there is no published research on damage detection of large-scale structures based on the system identification approach using both wavelets and neural networks. Recently, the authors developed a multiparadigm dynamic time-delay fuzzy wavelet neural network (WNN) model for non-parametric identification of structures using the non-linear autoregressive moving average with exogenous (NARMAX) inputs [41]. In addition, an adaptive Levenberg-Marquardt-least-squares (LM-LS) algorithm with a backtracking inexact linear search scheme was developed for training of the 609 dynamic fuzzy WNN model [42].…”

Section: Introductionmentioning

confidence: 99%

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

Jiang

Adeli

2007

Numerical Meth Engineering

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230

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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“…The general discrete dynamic input-output mapping in the dynamic fuzzy WNN approach is expressed as follows [41]:…”

Section: Dynamic Fuzzy Wnn Model For Damage Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Jiang

Adeli

2007

Numerical Meth Engineering

Self Cite

230

158

View full text Add to dashboard Cite

show abstract

“…The natural path of a solution of an existing condition is introduction of different heuristic procedures structural identification which considers features of a studied problem. They are grounded on an application of neural networks, intellectual and genetic technologies [6][7][8][9][10][11][12][13]. Application of these technologies is grounded on learning of their elements by means of search models-applicants and obtaining of total adequate model.…”

Section: Introductionmentioning

confidence: 99%

Structural Methods of Estimation Lyapunov Exponents Linear Dynamic System

Karabutov¹

2015

IJISA

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Abstract-The problem of structural identification linear dynamic systems on the basis of the analysis Lyapunov exponent in the conditions of uncertainty is considered. The method of estimation the general solution system on the basis of application static model is developed. Definition of Lyapunov exponent (LE) on the analysis of a coefficient structural properties system is grounded. On the basis of a coefficient of structural properties the special structures reflecting change LE are introduced. The criterion of estimation an order system on the basis of the analysis behaviour these structures are offered. The decision-making method about type of roots dynamic system on the basis of the analysis of time series and the structures reflecting change LE is developed. Two approaches to an estimation of the largest LE and the Perron bottom indexes are offered. The first approach to identification of a change in a coefficient of structural properties with the help secant method for various classes of roots is grounded. The second approach is the structurally-frequency method grounded on definition of estimations LE by means of the analysis of local minima of structures offered in work. The frequency method which is a modification of a method a bar graph in the statistical theory is applied to a validation of the obtained estimations. Results of simulation confirm effectiveness of the offered methods, structures and procedures.

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“…BHM at a global level using dynamic system parameters has been one of the most important approaches, and also has been intensively studied (e.g., Rizos et al 1990, Doebling et al 1996, Shifrin and Ruotolo 1999, Adeli and Jiang 2006, Siringoringo and Fujino 2006, Ni et al 2008. The basic idea behind BHM using the dynamic system parameters is that frequency and damping characteristics, as well as mode 2 shapes may provide useful information for the current health condition of bridges.…”

Section: Introductionmentioning

confidence: 99%

Drive-by bridge inspection from three different approaches

Kim¹,

Isemoto²,

McGetrick³

et al. 2014

Smart Structures and Systems

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Abstract. This study presents a vibration-based health monitoring strategy for short span bridges utilizing an inspection vehicle. How to screen the health condition of short span bridges in terms of a drive-by bridge inspection is described. Feasibility of the drive-by bridge inspection is investigated through a scaled laboratory moving vehicle experiment. The feasibility of using an instrumented vehicle to detect the natural frequency and changes in structural damping of a model bridge was observed. Observations also demonstrated the possibility of diagnosis of bridges by comparing patterns of identified bridge dynamic parameters through periodical monitoring. It was confirmed that the moving vehicle method identifies the damage location and severity well.

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Dynamic Fuzzy Wavelet Neural Network Model for Structural System Identification

Cited by 318 publications

References 33 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

Structural Methods of Estimation Lyapunov Exponents Linear Dynamic System

Drive-by bridge inspection from three different approaches

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