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Guo Siyu

Bio: Guo Siyu is an academic researcher from Hunan University. The author has contributed to research in topics: Fast Fourier transform & Spectral leakage. The author has an hindex of 7, co-authored 20 publications receiving 312 citations.

Papers
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Journal ArticleDOI
He Wen1, Junhao Zhang1, Meng Zhuo1, Guo Siyu1, Li Fuhai1, Yuxiang Yang 
TL;DR: This paper proposes a simple symmetrical interpolation FFT algorithm, where the even terms are removed from the fitting polynomial based on the triangular self-convolution windows (TSCW).
Abstract: Harmonic estimation is an important topic in power system signal processing. Windowed interpolation fast Fourier transformation (WIFFT) is an efficient algorithm for power system harmonic estimation, which can eliminate the errors caused by spectral leakage and picket fence effect. However, the fitting polynomial in the interpolation procedure contains both even and odd terms, and this increases the computational burden. This paper proposes a simple symmetrical interpolation FFT algorithm, where the even terms are removed from the fitting polynomial based on the triangular self-convolution windows (TSCW). The polynomials for frequency and amplitude computations are provided. Considerable leakage errors and harmonic interferences can be suppressed by the TSCW. Accurate estimations of harmonic parameters can be obtained via the fitting polynomial and the TSCW, both with adjustable order to fulfill different accuracy and speed requirements of practical power harmonic measurement. Simulation results and measurements have validated the proposed method.

110 citations

Journal ArticleDOI
He Wen1, Guo Siyu1, Zhaosheng Teng1, Li Fuhai1, Yuxiang Yang 
TL;DR: In this paper, a triangular self-convolution window is used to estimate the frequency of power signals corrupted by a stationary white noise and a simple analytical expression for the variance of noise contribution on the frequency estimation is derived, which shows the variances of frequency estimation are proportional to the energy of the adopted window.
Abstract: This paper focuses on the accurate frequency estimation of power signals corrupted by a stationary white noise. The noneven item interpolation FFT based on the triangular self-convolution window is described. A simple analytical expression for the variance of noise contribution on the frequency estimation is derived, which shows the variances of frequency estimation are proportional to the energy of the adopted window. Based on the proposed method, the noise level of the measurement channel can be estimated, and optimal parameters (e.g., sampling frequency and window length) of the interpolation FFT algorithm that minimize the variances of frequency estimation can thus be determined. The application in a power quality analyzer verified the usefulness of the proposed method.

70 citations

Journal ArticleDOI
TL;DR: A TSCW-based phase difference correction algorithm for calculating the power system signal parameters, such as frequency, phase, and amplitude, is presented in this paper and can easily be implemented in embedded systems.
Abstract: Weak harmonic components can easily be obscured by nearby strong harmonics due to the spectral leakage in the power system. To obtain a window suitable for solving the problem, the triangular self-convolution window (TSCW) is constructed, with the triangular window being the parent window to take advantages of its narrow major lobe and simple computation. A TSCW-based phase difference correction algorithm for calculating the power system signal parameters, such as frequency, phase, and amplitude, is presented in this paper. The TSCW has a low peak sidelobe level, a high sidelobe rolloff rate, and a simple spectral representation. Leakage errors and harmonic interferences are thus considerably reduced by weighting samples with the TSCW. The TSCW-based phase difference correction algorithm is free of solving high-order equations, and the overall method can easily be implemented in embedded systems. The effectiveness of the method proposed was analyzed by means of computer simulations and practical experiments for multifrequency signals without noise and with quantization noise.

54 citations

Journal ArticleDOI
He Wen1, Zhaosheng Teng1, Guo Siyu1, Jingxun Wang1, Buming Yang1, Yi Wang1, Tao Chen1 
TL;DR: Hanning self-convolution window (HSCW) is proposed in this article to suppress the impacts of fundamental frequency fluctuation and white noise on harmonic parameter estimation, and the HSCW is advantageous over existing combined cosine windows in terms of harmonic analysis performance.
Abstract: The Hanning self-convolution window (HSCW) is proposed in this paper. And the phase difference correction algorithm based on the discrete spectrum and the HSCW is given. The HSCW has a low peak side lobe level, a high side lobe roll-off rate, and a simple spectrum representation. Hence, leakage errors and harmonic interferences can be considerably reduced by weighting samples with the HSCW, the parameter estimation by the HSCW-based phase difference correction algorithm is free of solving high order equations, and the overall method can be easily implemented in embedded systems. Simulation and application results show that the HSCW-based phase difference correction algorithm can suppress the impacts of fundamental frequency fluctuation and white noise on harmonic parameter estimation, and the HSCW is advantageous over existing combined cosine windows in terms of harmonic analysis performance.

37 citations

Journal ArticleDOI
TL;DR: A surface defects detection method based on improved YOLOv3 for sawn lumbers is proposed, which replaces the intersection over union (IoU) loss for non-maximum suppression (NMS), because it considers the overlap area, the center point, and the aspect ratio, and thus can reduce the repeated detection.
Abstract: Although one-stage detectors, for example, YOLOv3, SSD, and RefineDet, based on the convolutional neural networks (CNNs) have been widely used in object detection, their localization accuracy of the defects is still poor and the problem of repeated detection still occurs. This article proposes a surface defects detection method based on improved YOLOv3 for sawn lumbers. First, a Gaussian YOLOv3 is used to estimate the coordinates and the localization uncertainty of the prediction box. Then, the complete intersection over union (CIoU) loss function is adopted to replace the intersection over union (IoU) loss for non-maximum suppression (NMS), because it considers the overlap area, the center point, and the aspect ratio, and thus can reduce the repeated detection. Finally, this article establishes two data sets, that is, the rubber lumber data set containing four kinds of defects and the pine lumber data set containing two kinds of defects. In total, there are 16 633 images and 6705 annotated images in these two data sets. The effectiveness of the proposed method has been validated by experiments. Our data sets are available at https://github.com/WenHe-Hnu/sawn-lumber-dataset .

32 citations


Cited by
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01 Jan 2006

3,012 citations

Journal ArticleDOI
TL;DR: The way digital systems are being currently designed in these areas is comprehensively reviewed, and a critical analysis of how they could significantly benefit from new FPGA features is presented.
Abstract: Field programmable gate arrays (FPGAs) have established themselves as one of the preferred digital implementation platforms in a plethora of current industrial applications, and extensions and improvements are still continuously being included in the devices. This paper reviews recent advancements in FPGA technology, emphasizing the novel features that may significantly contribute to the development of more efficient digital systems for industrial applications. Special attention is paid to the design paradigm shift caused by the availability of increasingly powerful embedded (and soft) processors, which transformed FPGAs from hardware accelerators to very powerful system-on-chip (SoC) platforms. New analog resources, floating-point operators, and hard memory controllers are also described, because of the great advantages they provide to designers. Software tools are being strongly influenced by the design paradigm shift, which requires from them a much better support for software developers. Focusing mainly on this issue, recent advancements in software resources [intellectual property (IP) cores and design tools] are also reviewed. The impact of new FPGA features in industrial applications is analyzed in detail in three main areas, namely digital real-time simulation, advanced control techniques, and electronic instrumentation, with focus on mechatronics, robotics, and power systems design. The way digital systems are being currently designed in these areas is comprehensively reviewed, and a critical analysis of how they could significantly benefit from new FPGA features is presented.

136 citations

Journal ArticleDOI
He Wen1, Junhao Zhang1, Meng Zhuo1, Guo Siyu1, Li Fuhai1, Yuxiang Yang 
TL;DR: This paper proposes a simple symmetrical interpolation FFT algorithm, where the even terms are removed from the fitting polynomial based on the triangular self-convolution windows (TSCW).
Abstract: Harmonic estimation is an important topic in power system signal processing. Windowed interpolation fast Fourier transformation (WIFFT) is an efficient algorithm for power system harmonic estimation, which can eliminate the errors caused by spectral leakage and picket fence effect. However, the fitting polynomial in the interpolation procedure contains both even and odd terms, and this increases the computational burden. This paper proposes a simple symmetrical interpolation FFT algorithm, where the even terms are removed from the fitting polynomial based on the triangular self-convolution windows (TSCW). The polynomials for frequency and amplitude computations are provided. Considerable leakage errors and harmonic interferences can be suppressed by the TSCW. Accurate estimations of harmonic parameters can be obtained via the fitting polynomial and the TSCW, both with adjustable order to fulfill different accuracy and speed requirements of practical power harmonic measurement. Simulation results and measurements have validated the proposed method.

110 citations

Journal ArticleDOI
TL;DR: A novel adaptive algorithm for the PCC voltage feedforward to work well with the varied grid impedance is proposed and does not have to sacrifice the dynamic or the harmonics rejection performance, or to use the on or offline grid impedance estimation.
Abstract: The performance of the grid-connected inverter was affected by the uncertainty of the grid conditions including the background distortion and the grid impedance. Typically, the feedforward of the grid voltage at the point of common coupling (PCC) highly suppressed the grid current harmonics caused by the grid voltage distortion; however, the PCC grid usually had a nonnegligible grid impedance, and the PCC voltage feedforward aroused serious grid current harmonics or instability. This study proposes a novel adaptive algorithm for the PCC voltage feedforward to work well with the varied grid impedance. In the proposal, the band-pass filters at the harmonic frequencies are used to detect the variation of the grid impedance as well as to facilitate the adaptive PCC voltage feedforward. It is not necessary to inject an additional harmonic to estimate the grid impedance. The basic principles as well as the realization and logic of the proposed algorithm are detailed, and some selected waveforms are provided to verify the superior performance. Compared with the typical robust design or adaptive control, the proposed algorithm does not have to sacrifice the dynamic or the harmonics rejection performance, or to use the on or offline grid impedance estimation.

83 citations

Journal ArticleDOI
TL;DR: In this article, a fast recursive discrete Fourier transform (FRDFT) algorithm is used for efficient fundamental tracking of varying power system signals, which is embedded with a fuzzy-logic decision-making module for obtaining optimal protection settings in case of changing system conditions.
Abstract: The increasing penetration of distributed generators (DGs) in modern day power grids results in varying fault current levels and network scenarios which may affect the conventional overcurrent protection relays. This necessitates a protection scheme with efficient fault signal estimations and smart decision-making capabilities in case of unexpected events. In this paper, a novel, fast, and adaptive relay mechanism has been proposed for complete protection of radial distribution systems with DG penetration. A fast recursive discrete Fourier transform (FRDFT) algorithm is used here for efficient fundamental tracking of varying power system signals. The numerical relay design using the FRDFT algorithm is embedded with a fuzzy-logic decision-making module for obtaining optimal protection settings in case of changing system conditions. The proposed adaptive scheme is tested on a standard IEEE 34-bus distribution system equipped with DGs by simulating various case studies. Simulation results verify that the adaptive relay is able to capture the changing system scenarios and select the protection settings accordingly.

76 citations