Analysis of the use of the Hanning Window for the measurement of interharmonic distortion caused by close tones in IEC standard framework.

Arranz-Gimon, Angel; Zorita-Lamadrid, Ángel L.; Moriñigo-Sotelo, Daniel; Duque-Pérez, Óscar

doi:10.1016/j.epsr.2022.107833

Cited by 8 publications

(2 citation statements)

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“…As mentioned in Section I, the use of the DFT on a time frame of 200 ms, when the analysed signal contains components with frequencies not integer multiple of 5 Hz, produces inaccurate results due to the spectral leakage [28]- [32]. In fact, in these cases, since the periodicity of the signal is longer than 200 ms, the portions of the signal analysed in two adjacent 200 ms time frames differ among them.…”

Section: Measurementsmentioning

confidence: 99%

The Use of Voltage Transformers for the Measurement of Power System Subharmonics in Compliance With International Standards

Crotti

D’Avanzo²,

Letizia

et al. 2022

IEEE Trans. Instrum. Meas.

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Section: Measurementsmentioning

confidence: 99%

The Use of Voltage Transformers for the Measurement of Power System Subharmonics in Compliance With International Standards

Crotti

D’Avanzo²,

Letizia

et al. 2022

IEEE Trans. Instrum. Meas.

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“…Figure 2 shows that the Hanning window's main lobe has been expanded and lowered while the side lobe has been drastically reduced. Hanning windows outperform rectangular windows in terms of decreasing leakage [14]. The analytical bandwidth widens and the frequency resolution decreases when the Hanning window's main lobe is extended.…”

Section: [] 0mentioning

confidence: 99%

Digital frequency spectrum analysis based on discrete Fourier transform

Tang

2022

International Conference on Network Communication and Information Security (ICNCIS 2022)

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Digital frequency spectrum analysis is widely used in signal processing and analyzing, which indicates the physical information and characteristics of components in a signal. According to the Nyquist sampling theorem, a sampling procedure is required to convert a continuous time signal into a discrete time signal, and the sampling rate should be more than twice the signal's maximum frequency. After sampling, windowing is used to truncate the signal and avoid spectrum leakage. Different windows are applied in different situations due to their different function expressions with different characteristics and they have different main lobe width and different side lobe levels. Discrete Fourier transform (DFT) process is needed to sample the signal after windowing. N-point DFT means sampling () j w Xe  with the interval of 2/ N  but the larger N does not guarantee a better performance of DFT signal. Fast Fourier transform (FFT) is a fast algorithm to calculate the DFT and often used in signal processing technology because of its obvious advantages of small computation and fast calculation. There are two typical functions in MATLAB which carry the FFT sequence with different functions. This paper introduces basic definitions of sampling and using Nyquist sampling theorem to determine sampling rate, compares different window functions and discusses how DFT length effect the frequency spectrum analysis.

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