Journal ArticleDOI
Structural Damage Identification Using Improved RBF Neural Networks in Frequency Domain
Rajendra Machavaram,K. Shankar +1 more
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TLDR
The novel improved RBF network is shown to be a good damage identification strategy for multiple member structures compared to conventional RBF and existing hybrid methods in terms of accuracy and computational effort.Abstract:
This paper presents a novel two stage improved Radial basis function (RBF) neural network for the damage identification of multimember structures in the frequency domain. The improvement of the proposed RBF network is carried out in two stages, viz. (i) first stage damage prediction by conventional RBF network trained with effective input-output patterns and (ii) in the second stage, minimization of the prediction error below the predefined error tolerance (3%) by training the network with patterns from reduced search space located after the first stage prediction. The network effective input patterns are fractional frequency change ratios (FFCs) and damage signature indices (DSIs), and the corresponding output patterns are stiffness values or damage severity of the structure at different damage levels. A Latin hypercube search (LHS) technique is used for finding the effective input-output patterns from the search space to improve the training efficiency. The numerical simulation of structural damage iden...read more
Citations
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Journal ArticleDOI
Machine learning for structural engineering: A state-of-the-art review
TL;DR: An overview of ML techniques for structural engineering is presented in this article with a particular focus on basic ML concepts, ML libraries, open-source Python codes, and structural engineering datasets.
Journal ArticleDOI
Vibration suppression of printed circuit boards using an external particle damper
TL;DR: In this article, the use of particle damper capsule on a Printed Circuit Board (PCB) and the development of Radial Basis Function neural network to accurately predict the acceleration response is presented.
Journal ArticleDOI
Improved Complex-valued Radial Basis Function (ICRBF) neural networks on multiple crack identification
M. Rajendra,K. Shankar +1 more
TL;DR: The results proved that, the proposed ICRBF and real-valued Improved RBF (IRBF) neural networks have identified the single and multiple cracks with less than 1% absolute mean percentage error as compared to conventional CRBF and RBF neural networks, mainly because of their second stage reduced search space moving technique.
Journal ArticleDOI
Application of RBF neural network in prediction of particle damping parameters from experimental data
TL;DR: In this article, a radial basis function (RBF) neural network was used to predict the modal damping ratio of a particle damping system using system input parameters such as particle size, particle density, packing ratio, and their effect at different modes of vibration.
Journal ArticleDOI
Experimental and numerical studies on a test method for damage diagnosis of stay cables
TL;DR: In this article, a vibration-based model-free damage diagnosis method of stay cables using the changes in natural frequencies is further proposed and validated, and a structural model is used to diagnose the state of stay cable.
References
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Journal ArticleDOI
Uncertainty handling in structural damage detection using fuzzy logic and probabilistic simulation
M. Chandrashekhar,Ranjan Ganguli +1 more
TL;DR: In this paper, a fuzzy logic system (FLS) with a new sliding window defuzzifier is developed for damage detection in a steel beam having material uncertainty (elastic modulus) with coefficient of variation (COV) of 3 percent and noise level of 015 in the measurement data, correctly identifies the fault with an accuracy of about 94 percent.
Journal ArticleDOI
Structural damage detection in a helicopter rotor blade using radial basis function neural networks
TL;DR: In this article, a neural network approach is used for detection of structural damage in a helicopter rotor blade using rotating frequencies of the flap (transverse bending), lag (in-plane bending), elastic torsion and axial modes.
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Recursive Least-Squares Time Domain Identification of Structural Parameters
Journal ArticleDOI
Structural damage detection and identification using fuzzy logic
James P. Sawyer,Singiresu S. Rao +1 more
TL;DR: In this paper, a general methodology for structural fault detection using fuzzy logic is presented based on monitoring the static, eigenvalue, and dynamic responses to determine the health status of a structure or machine.
Journal ArticleDOI
Constructing input vectors to neural networks for structural damage identification
Yq Q. Ni,Bs S. Wang,Jm M. Ko +2 more
TL;DR: In this paper, the authors propose a hierarchical neural network for structural damage location and extent detection. But, the network is trained using one-level damage samples to locate the position of damage and then re-trained by an incremental weight update method to estimate the damage extent.