An Improved Tuning Control Algorithm Based on SVD for FID Signal
Author(s) -
Huan Liu,
Hao Dong,
Jian Ge,
Pei Pei Guo,
Bing Bai,
Cheng Zhang
Publication year - 2017
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2017.p0133
Subject(s) - singular value decomposition , computer science , algorithm , signal (programming language) , fast fourier transform , programming language
The free induction decay (FID) quality signal of a proton precession magnetometer is closely related to tuning precision. To solve the commonly used current tuning problem method, we propose improving control algorithm tuning based on singular value decomposition (SVD). The space matrix is constructed by acquiring an analog-to-digital converter (ADC) for untuned FID signals, then conducting SVD to eliminate noise and obtain a useful signal. The fast Fourier transform (FFT) is then applied to the denoised FID signal to extract the time-frequency feature. Based on theory analysis, simulation modeling and actual FID signal testing, results show that compared to general tuning methods such as peak detection and auto correlation, our proposed algorithm improves sensor tuning precision and shortens tuning process time to one second or less.
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