Nonlinear characteristics analysis of sodium flow measurement based on the principle of turbulent fluctuation

2020 ◽  
Vol 368 ◽  
pp. 110834
Author(s):  
Xin-Long Yu ◽  
Ke-Jun Xu ◽  
Wen-Kai Wu ◽  
Xiao-Xue Yan ◽  
Ya Huang
Author(s):  
Oleksandr Ihorovich Parfeniuk ◽  
Oleksandr Mykolaiovych Naumchuk ◽  
Olena Olehivna Poliukhovych ◽  
Pawel Mazurek

It is proposed the technology of intellectual measurement of expenses with the use of an artificial neural network for overcoming the constraints caused by nonlinear characteristics of ultrasonic flowmeters. It is presented structural scheme of the proposed technology and structure of the model of the neural network


Author(s):  
Choluk Ri ◽  
Chunghyok Chae ◽  
Kwanggyun Sin ◽  
Yongil Sin ◽  
Kwangil Ri ◽  
...  

In this paper, based on the theory of rotor dynamics, the nonlinear dynamics of a rotor system with an eccentric rotor is analyzed. Taking the double-support rotor system with a single turntable as the object, the mathematical modeling method of the rotor system with an eccentric rotor and the rotation analysis of the turntable are analyzed in detail. According to ANSYS software, the influence of eccentricity on the rotor system and the relationship between eccentricity and nonlinearity are analyzed.


2020 ◽  
pp. 002029402091987 ◽  
Author(s):  
Jie Chen ◽  
Yun Cao ◽  
Chengyi Wang ◽  
Bin Li

Vortex flowmeter is a commonly used flow measurement device. It is almost not affected by the density and viscosity of the fluid, so the vortex flowmeter can be used for the detection of various medium, such as gas, liquid and steam. When dealing with vortex street signal, we usually use fast Fourier transform to calculate the signal frequency, but this traditional vortex street signal processing method is not only inefficient, but also difficult to filter out noise signals in the same frequency band as the vortex signal. The sparse Fourier transform utilizes the sparsity of the signal to efficiently calculate the signal spectrum, and the computational complexity is lower than that of the fast Fourier transform algorithm. In this paper, the amplitude and frequency of the vortex signal is analyzed by sparse Fourier transform and the noise signal is removed based on the amplitude–frequency characteristics of the vortex signal. Finally, by comparing with the other methods, we found that the time complexity of our algorithm is one-tenth of others’ methods. This means that our approach is 10 times faster than others.


1991 ◽  
Vol 88 (9) ◽  
pp. 905-911
Author(s):  
C.A.A. Jonker ◽  
J. Vermeij

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