1. School of Artificial Intelligence, Hebei University of Technology, Tianjin 300130, China 2. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
A combining detection method of all-phase fast Fourier transform (apFFT) and analytical mode decomposition was proposed aiming at the harmonic/interharmonic problem with dense frequency in power harmonic signals. Since AMD needs to determine the frequency components in the signal before decomposing, apFFT was used to perform spectrum analysis on the analyzed signals to obtain the values of the frequencies in the spectrum. The flat characteristics of the apFFT phase spectrum were used to determine whether the signal contains dense spectrum frequency component, and the approximate position of dense spectrum harmonic/interharmonic frequency was obtained. If there were dense spectral components, the dense spectrum segment of the signal was optimized by using quantum particle swarm to find the best binary frequency. The power harmonic signal was decomposed into a series of single-frequency signal components through the binary frequency between each frequency component by using AMD method in order to complete the measurement of harmonics with dense frequency. The method is better for the decomposition of harmonic/interharmonic signals with dense frequency compared with Hilbert-Huang transform (HHT) method. The simulation and experimental results showed the effectiveness and accuracy of the proposed method.
Shu-guang SUN,Peng TIAN,Tai-hang DU,Jing-qin WANG. Dense frequency harmonic/interharmonic detection based on apFFT-AMD. Journal of ZheJiang University (Engineering Science), 2020, 54(1): 178-188.
Fig.2All-phase fast Fourier transform amplitude and phase spectrum of single-frequency signals and dense-spectrum signals
Fig.3Diagram of binary frequency
Fig.4ApFFT-AMD flow chart of algorithm
成分
f/Hz
I/A
θ/（°）
间谐波
20.0
1
10
基波
50.2
15
30
谐波
100.4
8
200
间谐波
228.0
4
100
间谐波
520.0
2
250
Tab.1Signal parameters of example 1
Fig.5Amplitude spectrum of signal
Fig.6Phase spectrum of signal
Fig.7Original signal and decomposition results of this paper
Fig.8Decomposition results of EMD
分量
本文方法
EMD
fe/Hz
ξf/%
Ie/A
ξI/%
fe/Hz
ξf/%
Ie/A
ξI/%
1
20.07
0.35
1.04
4.00
19.92
0.40
0.86
14.00
2
50.08
0.24
14.96
0.27
49.92
0.56
14.28
4.80
3
99.95
0.45
7.99
0.13
99.92
0.48
8.00
0.00
4
228.00
0.00
4.00
0.00
227.93
0.03
3.96
1.00
5
519.98
0.01
2.00
0.00
519.91
0.02
2.00
0.00
Tab.2Parameter detection results of each component with proposed method and EMD
成分
f/Hz
I/A
θ/（°）
间谐波
20
1
10
基波
50
15
30
间谐波
160
1
200
间谐波
162
2
100
谐波
250
6
250
Tab.3Signal parameters of example 2
Fig.9Amplitude spectrum of signal
Fig.10Phase spectrum of signal
Fig.11Trend graph of fitness value and particle position
Fig.12Original signal and decomposition results of this paper
Fig.13Decomposition results of EMD
Fig.14Instantaneous amplitude and frequency of single-frequency signal components
Fig.15Semi-physical overall scheme of experiment
Fig.16Semi-physical experimental equipment
成分
f/Hz
I/A
θ/（°）
间谐波
25
2
20
基波
50
20
80
谐波
150
10
200
间谐波
152
3
90
谐波
250
8
250
Tab.4Specific parameters of signal model
Fig.17Amplitude spectrum of measured current signal
Fig.18Phase spectrum of measured current signal
Fig.19Measured current signal and decomposition results of this paper
Fig.20Instantaneous amplitude and frequency of single frequency component of measured current signal
分量
fe/Hz
ξf/%
Ie/A
ξI/%
$x_1$
24.99
0.04
1.98
1.00
$x_2$
50.00
0.00
19.84
0.80
$x_3$
150.00
0.00
9.91
0.90
$x_4$
151.98
0.01
2.98
0.67
$x_5$
250.00
0.00
7.93
0.88
Tab.5AMD parameter detection results of each component
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