NCAFI: Nuttall convolution window all-phase FFT interpolation-based harmonic detection algorithm for infrared imaging detection

Deng, Yi; Zhao, Guojin; Zhu, Kuihu; Zhou, Tao; Xu, Zhaixin

doi:10.1016/j.infrared.2022.104310

Cited by 8 publications

(6 citation statements)

References 37 publications

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“…In this paper, we propose a harmonic measurement algorithm based on a Blackman window to obtain higher estimation accuracy. It is supposed that a single frequency signal x(t) has frequency f 0 , amplitude A, sampling points n, and initial phase  is obtained a discrete signal of the following form after an analog-to-digital transformation with sampling rate f s as shown in Equations (6).…”

Section: Improved Blackman Window Harmonic Detection Methodsmentioning

confidence: 99%

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The Bi-Directional Metering Method Based on Improved Blackman Window Harmonic Detection

Wang,

Li,

Guo

et al. 2024

Frontiers in Artificial Intelligence and Applications

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In recent years, we have vigorously developed new energy power generation to help reduce carbon emissions in the power grid and respond to the national dual carbon goals. However, the grid connection of new energy generation will generate a large number of harmonics, leading to many problems in traditional energy metering schemes. In the paper, we propose an improved bi-directional metering method with harmonic detection. Firstly, an improved harmonic detection method with a Blackman window is proposed for a large number of harmonics present in the grid. Then, based on the harmonic detection results, a new energy measurement scheme is constructed, in which the strategies of user compensation and harmonic penalty are considered, and a new solution for user electricity billing is provided. Finally, the effectiveness and applicability were verified through numerical analysis.

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Section: Improved Blackman Window Harmonic Detection Methodsmentioning

confidence: 99%

“…Fast Fourier transform (FFT) [4][5] is the most widely used method. However, FFT often occurs in the process of harmonic analysis because the signal frequency always keeps changing, and non-integer period sampling occurs, which generates spectral leakage and fence effect and makes the detection results have large errors [6] .…”

Section: Introductionmentioning

confidence: 99%

The Bi-Directional Metering Method Based on Improved Blackman Window Harmonic Detection

Wang,

Li,

Guo

et al. 2024

Frontiers in Artificial Intelligence and Applications

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“…If the input signal is the x( n f s ) mentioned above, after MSD Self-Convolutional window ApCoSaMP, the sampling interval will be expanded to n∈(−N + 1, N − 1). According to [30], the weighted superimposed data y w (n) can be expressed as:…”

Section: All-phase Pretreatmentmentioning

confidence: 99%

“…g(α) = 6.21345707 + 1.32899884α 2 + 0.16442021α 4 + 0.01532052α 6 (30) Due to the phase invariance of ApCoSaMP, the phase value of the principal spectrum line of ApCoSaMP can be directly taken as the initial phase φ 0 of the signal, and more accurate measurement results can be obtained without correction.…”

Section: Parameter Correction Formulamentioning

confidence: 99%

Supraharmonic Detection Algorithm Based on Interpolation of Self-Convolutional Window All-Phase Compressive Sampling Matching Pursuit

Ji,

Yan,

Wang

2024

Information

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With the increase in the use of high-frequency power electronic devices, the harmonics injected into the power grid show a trend of high-frequency development. The continuous rise of the supraharmonic emission level in the distribution network has become one of the power quality problems that needs to be solved urgently in the power grid. In this paper, an algorithm based on the Interpolation of the Self-convolutional Window All-phase Compressive Sampling Matching Pursuit (ISWApCoSaMP) is proposed. Firstly, the self-convolution operation is used for the maximum sidelobe decay (MSD) window, and then the compressed sampling matching pursuit model based on the All-phase is constructed, leading to the All-phase Compressive Sampling Matching Pursuit (ApCoSaMP). Finally, the four-spectrum-line interpolation is combined to utilize spectrum line information to improve the accuracy of signal parameter detection in the frequency domain. The introduced All-phase greatly improves the phase measurement accuracy because the initial phase of the supraharmonic signal is selected for phase estimation. In addition, the self-convolutional window and four-spectrum-line interpolation make full use of the information in the time and frequency domains, thus optimizing the measurement results of amplitude and frequency. The algorithm achieves high accuracy in the measurement results of simulated signals and accurately measures supraharmonics.

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“…And high-precision detection and analysis of the harmonics is significant [1][2][3][4][5]. Currently, the measures to detect the harmonics mainly including instantaneous reactive power theory [6], wavelet analysis [7], S-Transform [8] and Fourier analysis [9][10][11]. Instantaneous reactive power theory obtains the fundamental and harmonic components based on the theory of inter-phase time-domain transformation.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of high-precision power harmonics detection system based FFT-FT

Tao,

Zhu,

Chen

2024

Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023)

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This paper proposed a high-precision and high-order power voltage harmonics detection method based on STM32H7. The system which uses STM32H7 as the core utilizes FFT-FT algorithm to find the peak of panoramic spectrum to further refine the spectrum and compensate amplitude error, so as to achieve high precision real-time power voltage harmonics measurement. The input voltage is attenuated, amplified whose gain is programmed, and input into STM32 MCU after digital-to-analog. Then, the harmonic amplitude is measured through searching the fundamental frequency after the FFT of voltage signal. This system adopts one-dimensional linear search algorithm to improve its real-time performance. The actual test results show the absolute error is less than or equal to 0.01Hz and the relative error is less than 0.03% for the frequency measurement in the range of 40~70Hz AC voltage. And the harmonic amplitudes' absolute error of rectangular wave is less than or equal to 4mV. In particular, the relative error of the fundamental wave and the third harmonic is less than 0.5%, and the absolute error of the 63rd harmonic is only 1mV. Therefore, the system has the characteristics of high-orders of harmonic measurement, high precision of frequency and amplitude measurement, which can meet the application requirements of high precision and high order harmonics measurement in power system.

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NCAFI: Nuttall convolution window all-phase FFT interpolation-based harmonic detection algorithm for infrared imaging detection

Cited by 8 publications

References 37 publications

The Bi-Directional Metering Method Based on Improved Blackman Window Harmonic Detection

The Bi-Directional Metering Method Based on Improved Blackman Window Harmonic Detection

Supraharmonic Detection Algorithm Based on Interpolation of Self-Convolutional Window All-Phase Compressive Sampling Matching Pursuit

Design and implementation of high-precision power harmonics detection system based FFT-FT

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