Fundamental detection for a power system based on SWT
DOI:DOI: 10.19783/j.cnki.pspc.211660
Key Words:fundamental detection  mode aliasing  SWT  Hilbert transform  noise resistance
Author NameAffiliation
TAO Jialan 1. Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan 430065, China
2. College of Science, Wuhan University of Science and Technology, Wuhan 430065, China
3. College of Information and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China 
YU Min 1. Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan 430065, China
2. College of Science, Wuhan University of Science and Technology, Wuhan 430065, China
3. College of Information and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China 
CHEN Guici 1. Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan 430065, China
2. College of Science, Wuhan University of Science and Technology, Wuhan 430065, China
3. College of Information and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China 
WANG Bin 1. Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan 430065, China
2. College of Science, Wuhan University of Science and Technology, Wuhan 430065, China
3. College of Information and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China 
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Abstract:When noise is mixed into a signal containing the fundamental component, the traditional time-frequency analysis method is prone to modal aliasing in the fundamental component extraction process. To accurately detect the fundamental component, synchrosqueezing wavelet transform (SWT) with high accuracy of time-frequency analysis is applied to realize the fundamental detection. First, the signal containing the fundamental component is decomposed into a set of intrinsic mode type functions (IMTs) by SWT. The first component IMT1 represents the fundamental. Then, the fundamental frequency and amplitude are measured by Hilbert Transform. Finally, the algorithm is verified in the situation of harmonic amplitude transient, noise mixing, fundamental frequency fluctuation and interharmonic frequencies near the fundamental and harmonic frequencies. The experimental results show that SWT can accurately extract the fundamental component, and the frequency accuracy can reach 10?8 orders of magnitude. The method has strong noise resistance and is better at extracting the fundamental component than harmonics and interharmonics. This work is supported by the National Natural Science Foundation of China (No. 51877161 and No. 61671338).
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