Sine wave fitting to short records initialized with the frequency retrieved from Hanning windowed FFT spectrum

Chen, Kui Fu; Xu, Cheng; Li, Yang Feng

doi:10.1016/j.measurement.2008.04.007

Cited by 24 publications

(11 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where [28]. It emphasizes that λ specifies the number of sinusoidal component cycles in the time window that comprises N signal samples.…”

Section: Frequency Estimation Using Maximum Decay Sidelobes Windowsmentioning

confidence: 99%

“…The method from [28] allows to determine the normalized frequency λ 1 (9), which considers the effect of a conjugate component with a frequency of -λ 1 (Fig. 1).…”

Section: Frequency Estimation Using Maximum Decay Sidelobes Windowsmentioning

confidence: 99%

“…These methods include the group of multi-point weighted interpolations of DFT methods (MWIDFT) [19], [20], [24] and a linear interpolation of the DFT (LIDFT) [25]- [27], based on an approximation of the unit circle by a polygon. This paper presents a generalization of the interpolation method MWDIFT [28] for maximum decay sidelobes windows at an arbitrary order, which allows to estimate the frequency of the fundamental sinusoidal component of a multi-frequency signal in a short measurement time (measurement of 0.5-2.5 measured signal cycles). This model is adequate for 50/60 Hz power signal which has harmonics and for time measurement requirements in renewable energy systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fast and Accurate Frequency Estimation for Renewable Energy Systems Using Maximum Decay Sidelobes Windows

Kania¹,

Borkowski²,

Mroczka³

2024

RE&PQJ

View full text Add to dashboard Cite

Abstract. Fast and accurate signal frequency estimation has great importance i.a. in renewable energy systems and power control systems. The energy produced by these systems shall fulfill quality requirements as defined in the respective directives and standards. More accurate and faster grid signal frequency estimation (which can be used to control the inverter) can improve the energy quality. This article presents an overview of methods for spectrum interpolation and signal frequency estimation and a generalized method for very accurate and fast frequency grid estimation by using the Fast Fourier Transform procedure and maximum decay sidelobes windows. An important feature of this algorithm is the elimination of the impact of the conjugate component on the estimation result. The article shows the statistical properties of the frequency estimator as well as the effect of noise for the estimation. The results of the simulation show that the algorithm can be successfully used for a fast and accurate estimation of the grid signal frequency i.a. in renewable energy systems and power control systems. The accuracy of the frequency estimation is in the order of 5·10 -11 Hz for a 5 ms measurement window. Using different windows from the discussed family allows to adjust to the actual requirements of estimation.

show abstract

“…where [28]. It emphasizes that λ specifies the number of sinusoidal component cycles in the time window that comprises N signal samples.…”

Section: Frequency Estimation Using Maximum Decay Sidelobes Windowsmentioning

confidence: 99%

“…The method from [28] allows to determine the normalized frequency λ 1 (9), which considers the effect of a conjugate component with a frequency of -λ 1 (Fig. 1).…”

Section: Frequency Estimation Using Maximum Decay Sidelobes Windowsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fast and Accurate Frequency Estimation for Renewable Energy Systems Using Maximum Decay Sidelobes Windows

Kania¹,

Borkowski²,

Mroczka³

2024

RE&PQJ

View full text Add to dashboard Cite

show abstract

“…In the fourth simulation, the very same noisy signal was considered for both current and voltage thus leading to a worst-case scenario. Despite of the added noise, no particular window was used since in this case rectangular windows -which are the same as having no window at all -provide the best results (Chen et al, 2009). Finally, the proposed methodology is applied to a practical ablation experience.…”

Section: ( ) ( ) ( ) P T V T I T =mentioning

confidence: 99%

A simple approach to calculate active power of electrosurgical units

et al. 2016

View full text Add to dashboard Cite

Introduction: Despite of more than a hundred years of electrosurgery, only a few electrosurgical equipment manufacturers have developed methods to regulate the active power delivered to the patient, usually around an arbitrary setpoint. In fact, no manufacturer has a method to measure the active power actually delivered to the load. Measuring the delivered power and computing it fast enough so as to avoid injury to the organic tissue is challenging. If voltage and current signals can be sampled in time and discretized in the frequency domain, a simple and very fast multiplication process can be used to determine the active power. Methods: This paper presents an approach for measuring active power at the output power stage of electrosurgical units with mathematical shortcuts based on a simple multiplication procedure of discretized variables -frequency domain vectors -obtained through Discrete Fourier Transform (DFT) applied on time-sampled voltage and current vectors. Results: Comparative results between simulations and a practical experiment are presented -all being in accordance with the requirements of the applicable industry standards. Conclusion: An analysis is presented comparing the active power analytically obtained through well-known voltage and current signals against a computational methodology based on vector manipulation using DFT only for time-to-frequency domain transformation. The greatest advantage of this method is to determine the active power of noisy and phased out signals with neither complex DFT or ordinary transform methodologies nor sophisticated computing techniques such as convolution. All results presented errors substantially lower than the thresholds defined by the applicable standards.

show abstract

“…23 For this reason, several methods have been proposed in recent years that exhibit excellent resistance to image component interference. [23][24][25][26] One of the effective algorithms was proposed by Chen et al, 24 and Borkowski et al 25 further developed this approach, extending the range of application to maximum sidelobe decaying windows. In 2014, Belega et al 23 proposed an improved three-point interpolation algorithm that performs well in resisting image frequency component disturbances.…”

Section: Introductionmentioning

confidence: 99%

Frequency estimators with high resistance to interference from image frequency components

Zhou

Gan

Hong

et al. 2018

Journal of Algorithms & Computational Technology

View full text Add to dashboard Cite

This paper presents an improved frequency estimation algorithm based on the interpolated discrete Fourier transform. High-accurate frequency estimation can be achieved by taking the geometric mean of two independent estimates, which are derived from the real parts of the two largest spectral bins and the imaginary parts, respectively. In situations where only a small number of sine wave cycles are observed, the ability of the algorithm to cancel interference from image frequency components results in improvements in accuracy. The residual errors of the proposed algorithm have been theoretically analyzed with maximum side-lobe decaying windows, since the windows have simple and uniform analytical expression of interpolation algorithm. The performance of the proposed algorithm was investigated using both Hanning and three-term maximum side-lobe decaying windows. A comparative analysis of systematic errors and noise sensitivity was performed between the new algorithm and traditional algorithms. Both the root mean squared error and the probability density of the errors were investigated under noisy conditions. Simulation results demonstrated that the new algorithm is not only highly resistant to interference from image components but is also resistant to the effects of random noise. The results presented in the paper are useful for identifying the best choice of algorithm in practical engineering applications.

show abstract

Sine wave fitting to short records initialized with the frequency retrieved from Hanning windowed FFT spectrum

Cited by 24 publications

References 38 publications

Fast and Accurate Frequency Estimation for Renewable Energy Systems Using Maximum Decay Sidelobes Windows

Fast and Accurate Frequency Estimation for Renewable Energy Systems Using Maximum Decay Sidelobes Windows

A simple approach to calculate active power of electrosurgical units

Frequency estimators with high resistance to interference from image frequency components

Contact Info

Product

Resources

About