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Automatic Parametric Fault Detection in Complex Microwave Filter Using SVM and PCA

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Cybernetics and Automation Control Theory Methods in Intelligent Algorithms (CSOC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 986))

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Abstract

The aim of this paper is to present the diagnostics of complex linear analog systems with parametric faults, using Support Vector Machine (SVM) as a tool for fault location. The diagnostic results of a microwave filter with the help of SVM network are presented. A strategy for finding the optimal kernels and their parameters for the particular system under test is proposed. A method for characteristic points reduction based on the statistical PCA method is also presented.

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Author information

Authors and Affiliations

  1. Warsaw University of Life Sciences, Nowoursynowska 159, Warsaw, Poland

    Adrian Bilski

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  1. Adrian Bilski
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Correspondence to Adrian Bilski .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Bilski, A. (2019). Automatic Parametric Fault Detection in Complex Microwave Filter Using SVM and PCA. In: Silhavy, R. (eds) Cybernetics and Automation Control Theory Methods in Intelligent Algorithms. CSOC 2019. Advances in Intelligent Systems and Computing, vol 986. Springer, Cham. https://doi.org/10.1007/978-3-030-19813-8_30

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