Deep learning architectures for data-driven damage detection in nonlinear dynamic systems
The primary goal of structural health monitoring is to detect damage at its onset before it reaches a critical level. The in-depth investigation in the present work addresses deep learning applied to data-driven damage detection in nonlinear dynamic systems. In particular, autoencoders (AEs) and generative adversarial networks (GANs) are implemented leveraging on 1D convolutional neural networks. The onset of damage is detected in the investigated nonlinear dynamic systems by exciting random vibrations of varying intensity, without prior knowledge of the system or the excitation and in unsupervised manner. The comprehensive numerical study is conducted on dynamic systems exhibiting different types of nonlinear behavior. An experimental application related to a magneto-elastic nonlinear system is also presented to corroborate the conclusions.
Code (0)
등록된 구현이 없습니다.
Tasks
Structural Health MonitoringSimilar Papers 제목 키워드 기반
A Data-Driven Approach for Linear and Nonlinear Damage Detection Using Variational Mode Decomposition and GARCH Model
In this article, an original data-driven approach is proposed to detect both linear and nonlinear damage in structures using output-only responses. The method deploys variational mode decomposition (VMD) and a generalise…
Damage detection in an uncertain nonlinear beam based on stochastic Volterra series: an experimental application
The damage detection problem becomes a more difficult task when the intrinsically nonlinear behavior of the structures and the natural data variation are considered in the analysis because both phenomena can be confused …
Cantilever BeamNovelty DetectionDamage detection in an uncertain nonlinear beam based on stochastic Volterra series
The damage detection problem in mechanical systems, using vibration measurements, is commonly called Structural Health Monitoring (SHM). Many tools are able to detect damages by changes in the vibration pattern, mainly, …
input filteringStructural Health MonitoringMulti-resolution Dynamic Mode Decomposition for Damage Detection in Wind Turbine Gearboxes
We introduce an approach for damage detection in gearboxes based on the analysis of sensor data with the multi-resolution dynamic mode decomposition (mrDMD). The application focus is the condition monitoring of wind turb…
On the Detection and Quantification of Nonlinearity via Statistics of the Gradients of a Black-Box Model
Detection and identification of nonlinearity is a task of high importance for structural dynamics. Detecting nonlinearity in a structure, which has been designed to operate in its linear region, might indicate the existe…