Substructuring technique for damage detection using statistical multi-stage artificial neural network

QR Code

Substructuring technique for damage detection using statistical multi-stage artificial neural network

Artificial Neural networks (ANN) have been proven in many studies to be able to efficiently detect damage from vibration measurements. Their capability to recognize patterns and to handle non-linear and non-unique problems provides an advantage over traditional mathematical methods in correlating th...

Full description

Bibliographic Details
Main Authors:	Bakhary, N., Hao, Hong, Deeks, A.
Format:	Journal Article
Published:	Multi-Science Publishing Co. Ltd 2010
Online Access:	http://hdl.handle.net/20.500.11937/39148

Similar Items

Structure damage detection using neural network with multi-stage substructuring
by: Bakhary, N., et al.
Published: (2010)

The use of a non-probabilistic artificial neural network to consider uncertainties in vibration-based-damage detection
by: Padil, K., et al.
Published: (2017)

Vibration-based damage detection of slab structure using artificial neural network
by: Bakhary, Norhisham
Published: (2006)

Substructural Damage Detection With Incomplete Information of the Structure
by: Li, Jun, et al.
Published: (2012)

Substructure damage identification based on wavelet-domain response reconstruction
by: Li, Jun, et al.
Published: (2014)

Damage Detection of a Substructure Based on Response Reconstruction in Frequency Domain
by: Li, Jun, et al.
Published: (2013)

Numerical study of structural progressive collapse using substructure technique
by: Li, Jun, et al.
Published: (2013)

Multi-stage identification scheme for detecting damage in structures under ambient excitations
by: Bao, C., et al.
Published: (2013)

Damage identification in a substructure of a box-section girder
by: Li, Jun, et al.
Published: (2011)

Damage identification of a target substructure with moving load excitation
by: Li, Jun, et al.
Published: (2012)

Damage identification for multi-rotor drone using convolutional neural network technique
by: Ma, Yumeng
Published: (2023)

Substructure damage identification based on response reconstruction in frequency domain and model updating
by: Li, Jun, et al.
Published: (2012)

Univariate Artificial Neural Network In Forcasting Demand Of Low Cost House In Petaling Jaya
by: Bakhary, Norhisham, et al.
Published: (2004)

Variation of vibration properties of six RC slabs at different damage levels
by: Hao, Hong, et al.
Published: (2017)

Modeling of tool wear in drilling by statistical analysis and artificial neural network
by: SANJAY, C, et al.
Published: (2005)

Substructural interface force identification with limited vibration measurements
by: Li, Jun, et al.
Published: (2016)

Artificial neural network based autoregressive modeling technique with application in voice activity detection
by: Aibinu, Abiodun Musa, et al.
Published: (2012)

Application of artificial neural network on vibration test data for damage identification in bridge girder
by: S. J. S. Hakim*, S. J. S. Hakim*
Published: (2011)

Application of artificial neural network on vibration test data for damage identification in bridge girder
by: S. Hakim, S. J., et al.
Published: (2011)

Mining substructures in protein data
by: Hadzic, Fedja, et al.
Published: (2006)

Application of Artificial Neural Network in Detection of DOS Attacks
by: Ahmad, iftikhar, et al.
Published: (2009)

Application of Artificial Neural Network in Detection of Probing Attacks
by: I., Ahmad, et al.
Published: (2010)

Application of Artificial Neural Network in Detection of Probing Attacks
by: Ahmad, iftikhar, et al.
Published: (2009)

Multiple faults detection using artificial neural network
by: Abd. Hamid, Mohd. Kamaruddin
Published: (2004)

Face detection using artificial neural network approach
by: Khalid, Marzuki, et al.
Published: (2007)

Structural damage identification based on autoencoder neural networks and deep learning
by: Pathirage, C., et al.
Published: (2018)

Artificial neural network
by: Muhamad Nor, Norfarina, et al.
Published: (2016)

Damage detection of shear link conditions with multi-type measurements
by: Li, Jun, et al.
Published: (2016)

Application of artificial neural networks and multivariate statistics to estimate UCS using textural characteristics
by: Manouchehrian, A., et al.
Published: (2012)

Artificial Neural Network Approaches to Intrusion Detection: A Review
Published: (2009)

Artificial Neural Network Approaches to Intrusion Detection: A Review
by: Ahmad, Iftikhar
Published: (2009)

Artificial Neural Network Approaches to Intrusion Detection: A Review
by: Ahmad, iftikhar, et al.
Published: (2009)

Artificial Neural Network Approaches to Intrusion Detection: A Review
by: I., Ahmad, et al.
Published: (2010)

Edge detection of MRI images using artificial neural network
by: Gunawan, Teddy Surya, et al.
Published: (2017)

Substructural Response Reconstruction in Wavelet Domain
by: Li, Jun, et al.
Published: (2011)

Structural damage identification employing hybrid intelligence using artificial neural networks and vibration-based methods
by: S. Hakim, S. J., et al.
Published: (2022)

Evaluation of banana and pear fruit maturity stages using laser backscattering images, artificial neural network and support vector machine techniques
by: Emmanuel, Adebayo Segun
Published: (2017)

Modularity in artificial neural networks
by: Amer, Mohammed Elsayed Mohammed
Published: (2021)

Artificial neural network (ANN)
by: Kang, Miew How
Published: (2011)

Modeling and simulation of multi-stream heat exchanger using artificial neural network
by: Khan, M., et al.
Published: (2012)

Cannot write session to /tmp/vufind_sessions/sess_5lgk8sbssda7ddn5gpalb0tgkl