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Energies 2019, 12(6), 991; https://doi.org/10.3390/en12060991

Fault Detection of a Spherical Tank Using a Genetic Algorithm-Based Hybrid Feature Pool and k-Nearest Neighbor Algorithm

Department of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan 44610, Korea
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Received: 24 February 2019 / Revised: 9 March 2019 / Accepted: 11 March 2019 / Published: 14 March 2019
(This article belongs to the Special Issue Fault Diagnosis and Fault-Tolerant Control)
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Abstract

Fault detection in metallic structures requires a detailed and discriminative feature pool creation mechanism to develop an effective condition monitoring system. Traditional fault detection methods incorporate handcrafted features either from the time, frequency or time-frequency domains. To explore the salient information provided by the acoustic emission (AE) signals, a hybrid of feature pool creation and an optimal features subset selection mechanism is proposed for crack detection in a spherical tank. The optimal hybrid feature pool creation process is composed of two major parts: (1) extraction of statistical features from time and frequency domains, as well as extraction of traditional features associated with the AE signals; and (2) genetic algorithm (GA)-based optimal features subset selection. The optimal features subset is then provided to the k-nearest neighbor (k-NN) classifier to distinguish between normal (NC) and crack conditions (CC). Experimental results show that the proposed approach yields an average 99.8% accuracy for heath state classification. To validate the effectiveness of the proposed approach, it is compared to conventional non-linear dimensionality reduction techniques, as well as those without feature selection schemes. Experimental results show that the proposed approach outperforms conventional non-linear dimensionality reduction techniques, achieving at least 2.55% higher classification accuracy. View Full-Text
Keywords: acoustic emissions; fault diagnosis; genetic algorithm; hybrid feature pool; k-NN classifier; spherical tank; statistical features acoustic emissions; fault diagnosis; genetic algorithm; hybrid feature pool; k-NN classifier; spherical tank; statistical features
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Hasan, M.J.; Kim, J.-M. Fault Detection of a Spherical Tank Using a Genetic Algorithm-Based Hybrid Feature Pool and k-Nearest Neighbor Algorithm. Energies 2019, 12, 991.

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