Browsing by Author "Inman D."
Now showing items 1-7 of 7
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1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data
Abdeljaber O.; Avci O.; Kiranyaz M.S.; Boashash B.; Sodano H.; Inman D.J.... more authors ... less authors ( Elsevier B.V. , 2018 , Article)Structural damage detection has been an interdisciplinary area of interest for various engineering fields. While the available damage detection methods have been in the process of adapting machine learning concepts, most ... -
A New Benchmark Problem for Structural Damage Detection: Bolt Loosening Tests on a Large-Scale Laboratory Structure
Avci O.; Abdeljaber O.; Kiranyaz, Mustafa Serkan; Hussein M.; Gabbouj M.; Inman D.... more authors ... less authors ( Springer , 2022 , Conference Paper)Monitoring the structural performance of engineering structures has always been pertinent for maintaining structural health and assessing the life cycle of structures. Structural Health Monitoring (SHM) and Structural ... -
Control of plate vibrations with artificial neural networks and piezoelectricity
Avci O.; Abdeljaber O.; Kiranyaz, Mustafa Serkan; Inman D. ( Springer New York LLC , 2020 , Conference Paper)This paper presents a method for active vibration control of smart thin cantilever plates. For model formulation needed for controller design and simulations, finite difference technique is used on the cantilever plate ... -
Convolutional neural networks for real-time and wireless damage detection
Avci O.; Abdeljaber O.; Kiranyaz, Mustafa Serkan; Inman D. ( Springer New York LLC , 2020 , Conference Paper)Structural damage detection methods available for structural health monitoring applications are based on data preprocessing, feature extraction, and feature classification. The feature classification task requires considerable ... -
Structural damage detection in real time: Implementation of 1D convolutional neural networks for SHM applications
Avci O.; Abdeljaber O.; Kiranyaz, Mustafa Serkan; Inman D. ( Springer , 2017 , Conference Paper)Most of the classical structural damage detection systems involve two processes, feature extraction and feature classification. Usually, the feature extraction process requires large computational effort which prevent the ... -
Structural health monitoring with self-organizing maps and artificial neural networks
Avci O.; Abdeljaber O.; Kiranyaz, Mustafa Serkan; Inman D. ( Springer New York LLC , 2020 , Conference Paper)The use of self-organizing maps and artificial neural networks for structural health monitoring is presented in this paper. The authors recently developed a nonparametric structural damage detection algorithm for extracting ... -
Vibration suppression in metastructures using zigzag inserts optimized by genetic algorithms
Avci O.; Abdeljaber O.; Kiranyaz, Mustafa Serkan; Inman D. ( Springer New York LLC , 2017 , Conference Paper)Metastructures are known to provide considerable vibration attenuation for mechanical systems. With the optimization of the internal geometry of metastructures, the suppression performance of the host structure increases. ...