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Article

A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE

Control, Modeling, Identification and Applications (CoDAlab), Department of Mathematics, Escola d’Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Campus Diagonal-Besòs (CDB), Eduard Maristany, 16, 08019 Barcelona, Spain
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This paper is an extended version of our paper published in International Conference on Structural Engineering Dynamics (ICEDyn 2019).
Sensors 2019, 19(23), 5097; https://doi.org/10.3390/s19235097
Received: 24 October 2019 / Revised: 20 November 2019 / Accepted: 20 November 2019 / Published: 21 November 2019
(This article belongs to the Special Issue Sensors for Structural Health Monitoring and Condition Monitoring)
This work presents a structural health monitoring (SHM) approach for the detection and classification of structural changes. The proposed strategy is based on t-distributed stochastic neighbor embedding (t-SNE), a nonlinear procedure that is able to represent the local structure of high-dimensional data in a low-dimensional space. The steps of the detection and classification procedure are: (i) the data collected are scaled using mean-centered group scaling (MCGS); (ii) then principal component analysis (PCA) is applied to reduce the dimensionality of the data set; (iii) t-SNE is applied to represent the scaled and reduced data as points in a plane defining as many clusters as different structural states; and (iv) the current structure to be diagnosed will be associated with a cluster or structural state based on three strategies: (a) the smallest point-centroid distance; (b) majority voting; and (c) the sum of the inverse distances. The combination of PCA and t-SNE improves the quality of the clusters related to the structural states. The method is evaluated using experimental data from an aluminum plate with four piezoelectric transducers (PZTs). Results are illustrated in frequency domain, and they manifest the high classification accuracy and the strong performance of this method. View Full-Text
Keywords: classification detection; principal component analysis (PCA); structural changes; structural health monitoring (SHM); t-distributed stochastic neighbor embedding (t-SNE) classification detection; principal component analysis (PCA); structural changes; structural health monitoring (SHM); t-distributed stochastic neighbor embedding (t-SNE)
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MDPI and ACS Style

Agis, D.; Pozo, F. A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE . Sensors 2019, 19, 5097. https://doi.org/10.3390/s19235097

AMA Style

Agis D, Pozo F. A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE . Sensors. 2019; 19(23):5097. https://doi.org/10.3390/s19235097

Chicago/Turabian Style

Agis, David, and Francesc Pozo. 2019. "A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE " Sensors 19, no. 23: 5097. https://doi.org/10.3390/s19235097

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