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المؤلفAvci O.
المؤلفAbdeljaber O.
المؤلفKiranyaz, Mustafa Serkan
تاريخ الإتاحة2022-04-26T12:31:17Z
تاريخ النشر2022
اسم المنشورConference Proceedings of the Society for Experimental Mechanics Series
المصدرScopus
المعرّفhttp://dx.doi.org/10.1007/978-3-030-75988-9_17
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85118193312&doi=10.1007%2f978-3-030-75988-9_17&partnerID=40&md5=54b7815adfb1a14bf6d0473b14249d2f
معرّف المصادر الموحدhttp://hdl.handle.net/10576/30582
الملخصThis paper presents a brief overview of vibration-based structural damage detection studies that are based on machine learning (ML) in civil engineering structures. The review includes both parametric and nonparametric applications of ML accompanied with analytical and/or experimental studies. While the ML tools help the system learn from the data fed into, the computer enhances the task with the learned information without any programming on how to process the relevant data. As such, the performance level of ML-based damage identification methodologies depends on the feature extraction and classification steps, especially on the classifier choices for which the characteristic nature of the acceleration signals is recorded in a feasible way. Yet, there are several issues to be discussed about the existing ML procedures for both parametric and nonparametric applications, which are presented in this paper.
اللغةen
الناشرSpringer
الموضوعComputer programming
Machine learning
Structural dynamics
Structural health monitoring
Structures (built objects)
'current
Civil engineering structures
Damage Identification
Damage localization
Learn+
Machine-learning
Nonparametrics
State of the art
Structural damage detection
Vibration-based method
Damage detection
العنوانStructural Damage Detection in Civil Engineering with Machine Learning: Current State of the Art
النوعConference Paper
الصفحات223-229
dc.accessType Abstract Only


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