scholarly journals Application of a Hybrid Method for Power System Frequency Estimation with a 0.2-Second Sampled Period

2018 ◽  
Author(s):  
Chih-Hung Lee ◽  
Men-Shen Tsai
Keyword(s):  
Power System ◽  
Frequency Domain ◽  
Fundamental Frequency ◽  
Hybrid Method ◽  
Amplitude Ratio ◽  
Frequency Estimation ◽  
Estimation Method ◽  
System Quality ◽  
Signal Processing Technique ◽  
Observation Window

The signal processing technique is one of the principal tools for diagnosing power quality (PQ) issues in electrical power systems. The Discrete Fourier Transform (DFT) is a frequency analysis technique used to process power system signals and identify PQ problems. However, the DFT algorithm may lead to spectral leakage and picket-fence effect problems for asynchronously sampled signals that contain harmonic, inter-harmonic, and flicker components. To resolve this shortcoming, a hybrid method for frequency estimation based on a second-level DFT approach and a frequency-domain interpolation algorithm to obtain the accurate fundamental frequency of a power system is proposed in this paper. This method uses a second-level DFT to compute the cosine and sine parts for the fundamental frequency components of the acquired signals. Then, a frequency-domain interpolation approach is adopted to determine the amplitude ratio for the cosine and sine parts of the system's fundamental frequency. To demonstrate the performance of the proposed frequency estimation method, the observation window used by this paper to evaluate different estimation algorithms is 200 ms. According to the IEC standards, a 200 ms acquisition window is recommended for power system quality assessment. A set of mixed signals with harmonic, inter-harmonic, and flicker components with the fundamental frequency deviation is used. The evaluation results demonstrate the superiority of the new method over other approaches for assessing asynchronously sampled signals contaminated with noise, harmonic, inter-harmonic, and flicker components.

scholarly journals Application of a Hybrid Method for Power System Frequency Estimation with a 0.2-second Sampled Period

2018 ◽  
Vol 201 ◽  
pp. 02007
Author(s):  
Chih-Hung Lee ◽  
Men-Shen Tsai
Keyword(s):  
Power Systems ◽  
Power System ◽  
Frequency Domain ◽  
Fundamental Frequency ◽  
Hybrid Method ◽  
Amplitude Ratio ◽  
Frequency Estimation ◽  
Electrical Power ◽  
Processing Technique ◽  
Signal Processing Technique

The signal processing technique is one of the principal tools for diagnosing power quality (PQ) issues in electrical power systems. The Discrete Fourier Transform (DFT) is a frequency analysis technique used to process power system signals and identify PQ problems. However, the DFT algorithm may lead to spectral leakage and picket-fence effect problems for asynchronously sampled signals that contain harmonic, inter-harmonic, and flicker components. To resolve this shortcoming, a hybrid method for frequency estimation based on a second-level DFT approach and a frequency-domain interpolation algorithm to obtain the accurate fundamental frequency of a power system is proposed in this paper. This method uses a second-level DFT to compute the cosine and sine parts for the fundamental frequency components of the acquired signals. Then, a frequency-domain interpolation approach is adopted to determine the amplitude ratio for the cosine and sine parts of the system’s fundamental frequency. A set of mixed signals with harmonic, inter-harmonic, and flicker components with the fundamental frequency deviation is used. The evaluation results demonstrate the superiority of the new method over other approaches for assessing asynchronously sampled signals contaminated with noise, harmonic, inter-harmonic, and flicker components.

scholarly journals Low-Latency f0 Estimation for the Finger Plucked Electric Bass Guitar Using the Absolute Difference Function

2020 ◽  
Vol 27 (4) ◽  
pp. 79-94
Author(s):  
Christhian Henrique Gomes Fonseca ◽  
Tiago Tavares
Keyword(s):  
Fundamental Frequency ◽  
Frequency Estimation ◽  
Estimation Method ◽  
Absolute Difference ◽  
Low Latency ◽  
Signal Acquisition ◽  
Electric Bass ◽  
Fundamental Frequency Estimation ◽  
Minimum Delay ◽  
Analog Instrument

Audio-to-MIDI conversion can be used to allow digital musical control through an analog instrument. Audio-to-MIDI converters rely on fundamental frequency estimators that are usually restricted to a minimum delay of two fundamental periods. This delay is perceptible for the case of bass notes. In this dissertation, we propose a low-latency fundamental frequency estimation method that relies on specific characteristics of the electric bass guitar. By means of physical modeling and signal  acquisition, we show that the assumptions of this method are based on the generalization of all electric basses. We evaluated our method in a dataset with musical notes played by diverse bassists. Results show that our method outperforms the Yin method in low-latency settings, which indicates its suitability for low-latency audio-to-MIDI conversion of the electric bass sound.

Power System Frequency Estimation Method in the Presence of Harmonics

2016 ◽  
Vol 65 (1) ◽  
pp. 56-69 ◽  
Author(s):  
Hui Xue ◽  
Maohai Wang ◽  
Rengang Yang ◽  
Yan Zhang
Keyword(s):  
Power System ◽  
Frequency Estimation ◽  
Estimation Method ◽  
System Frequency

A Hybrid Method for Power System Frequency Estimation

2012 ◽  
Vol 27 (3) ◽  
pp. 1252-1259 ◽  
Author(s):  
Jinfeng Ren ◽  
Mladen Kezunovic
Keyword(s):  
Power System ◽  
Hybrid Method ◽  
Frequency Estimation ◽  
System Frequency

scholarly journals Low-Latency f0 Estimation for the Finger Plucked Electric Bass Guitar Using the Absolute Difference Function

2019 ◽  
Author(s):  
Christhian Fonseca ◽  
Tiago Tavares
Keyword(s):  
Fundamental Frequency ◽  
Frequency Estimation ◽  
Estimation Method ◽  
Physical Modelling ◽  
Absolute Difference ◽  
Low Latency ◽  
Signal Acquisition ◽  
Electric Bass ◽  
Minimum Delay ◽  
Analog Instrument

Audio-to-MIDI conversion can be used to allow digital musical control by means of an analog instrument. Audio-to-MIDI converters rely on fundamental frequency estimators that are frequently restricted to a minimum delay of two fundamental periods. This delay is perceptible for the case of bass notes. In this paper, we propose a lowlatency fundamental frequency estimation method that relies on specific characteristics of the electric bass guitar. By means of physical modelling and signal acquisition, we show that the assumptions of the method relies on generalize throughout electric basses. We evaluate our method in a dataset with musical notes played by diverse bassists. Results show that our method outperforms the Yin method in low-latency settings, which indicates its suitability for low-latency audio-to-MIDI conversion of the electric bass sound.

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