Filtration of deteriorated signals used in the control systems by orthogonal wavelets

Todorova, Mariyana; Parvanova, Reneta

doi:10.1109/elma.2017.7955471

Cited by 5 publications

(1 citation statement)

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“…Wavelet transform is a relatively new concept, but it is one of the most popular time-frequency transformations (Todorova & Parvanova, 2017). While the Fourier transform expands the signals in terms of infinitely expanded sinuses and cosines, wavelet transform methods use distinct ripples that concentrate their energy over time or in space, generally an excessively enlarged point (Fan et al, 2012;Macedo et al, 2012).…”

Section: Wavelet De-noising Techniquementioning

confidence: 99%

3D Kısmi Deşarj Sinyal Grafikleri ile Yüksek Gerilim Ekipmanlarının Dielektrik Analizi

Serttaş¹,

Serttaş²

2021

European Journal of Science and Technology

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Partial discharge (PD) is a very critical phenomenon for high voltage engineering. Accurate measurements and detailed analysis of PD's are necessary to have a reliable electrical system. Therefore, the aim of obtaining graphics of PD signals is to visualize PD's to solve and analyze trend points. Unfiltered and scattered partial discharge signals cause false observations even though these are rigorously measured and calculated. Conventional graphic obtaining methods have some drawbacks, such as ignoring intensity areas that are significant to identify trend areas, misrepresenting the sequential partial discharge signals following each other, and causing high costs. In this sense, this paper proposes an improved and practical method using a multi-paradigm numerical computing programming language without needing expensive methods and tools. High voltage power cables are tested in the laboratory to record digital time-based PD signals. The experimentally measured PD data are converted into 2D and 3D graphics with the proposed technique. In this context, 2D and 3D graphics are compared, and the process of creating 3D graphics is explained. Consequently, the data becomes easy to understand and define with 3D graphics obtained using the method.

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Section: Wavelet De-noising Techniquementioning

confidence: 99%