A new phase difference measurement algorithm for extreme frequency signals based on discrete time Fourier transform with negative frequency contribution

2015 ◽  
Vol 86 (1) ◽  
pp. 015104 ◽  
Author(s):  
Ting’ao Shen ◽  
Yaqing Tu ◽  
Ming Li ◽  
Haitao Zhang
2012 ◽  
Vol 10 (5) ◽  
pp. 1270-1275 ◽  
Author(s):  
LV Chang-Zhi ◽  
Di Fan ◽  
Mao-Yong Cao ◽  
Qin-Guang Cai ◽  
Hong Yu

2015 ◽  
Vol 45 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Svetlin Stoyanov

Abstract An analytical solution for a specific case of the forced Duffing oscillator is proposed. The excitation force contains two harmonics with significant difference frequencies. This case corresponds to a presence of a defect in the machinery and is in the art of the machinery vibration diagnostics. The results obtained show an amplitude modulation. Therefore, the presence of an amplitude modulation in the vibration signal may be used as an indicator for a malfunction. Analytical solution derived clarifies how the amplitude modulation occurs. Also, a numerical solution is realized and compared with the analytical one. For this, the Duffing equation is solved numerically and then, the spectrograms of vibrations are obtained through a Discrete-time Fourier Transform.


2019 ◽  
Vol 19 (2) ◽  
pp. 48-52
Author(s):  
Nan Chen ◽  
Shangchun Fan ◽  
Dezhi Zheng

Abstract According to the characteristics of stable single-phase flow, a phase difference measurement method based on the extended Kalman filter is proposed in this paper for use with Coriolis mass flowmeters. Firstly, the Mallat algorithm is applied to filter out interference signals. Then, the frequency and phase difference of the two reconstructed signals are detected through the extended Kalman filter. Compared with the sliding Goertzel algorithm or discrete time Fourier transform, the proposed method does not need to predict the signal frequency and avoids quadratic error. Simulations and experiments show that the proposed method has stronger anti-interference, higher measurement accuracy and lower relative error than the existing method based on the Hilbert transformation.


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