دورية أكاديمية
A Novel Feature Extraction Method for Soft Faults in Nonlinear Analog Circuits Based on LMD-GFD and KPCA
| العنوان: | A Novel Feature Extraction Method for Soft Faults in Nonlinear Analog Circuits Based on LMD-GFD and KPCA |
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| المؤلفون: | Xinmiao Lu, Jiaxu Wang, Qiong Wu, Yuhan Wei, Yanwen Su |
| المصدر: | Tehnički Vjesnik, Vol 28, Iss 6, Pp 2121-2126 (2021) |
| بيانات النشر: | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek, 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Engineering (General). Civil engineering (General) |
| مصطلحات موضوعية: | Fault Feature Extraction, Generalized Fractal Dimension (GFD), Kernel Principal Component Analysis (KPCA), Local Mean Decomposition (LMD), Nonlinear Analog Circuit, Engineering (General). Civil engineering (General), TA1-2040 |
| الوصف: | To obtain feature information of soft faults in non-linear analog circuits in a more effective way, this paper proposed a novel feature extraction method for soft faults in non-linear analog circuits based on Local Mean Decomposition-Generalized Fractal Dimension (LMD-GFD) and Kernel Principal Component Analysis (KPCA). First, the fault signals were subject to LMD, the features of each component signal were extracted by GFD for the first time, and a high-dimensional feature space was formed. Then, KPCA was employed to reduce the dimensionality of the high-dimensional feature space, and feature extraction was performed again; at last, KPCA and Support Vector Machine (SVM) were adopted to diagnose the faults. The experimental results showed that the proposed LMD-GFD-KPCA method had effectively extracted the features of the soft faults in the non-linear analog circuits, and it achieved a high diagnosis rate. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1330-3651 1848-6339 |
| Relation: | https://hrcak.srce.hr/file/385034; https://doaj.org/toc/1330-3651; https://doaj.org/toc/1848-6339 |
| DOI: | 10.17559/TV-20210429033711 |
| URL الوصول: | https://doaj.org/article/a690d54cea884bb8af84bfe5df89b070 |
| رقم الأكسشن: | edsdoj.690d54cea884bb8af84bfe5df89b070 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 13303651 18486339 |
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| DOI: | 10.17559/TV-20210429033711 |