Stochastic resonance in a single-mode laser driven by quadratic pump noise and amplitude-modulated signal

This paper investigates the phenomenon of stochastic resonance in a single-mode laser driven by quadratic pump noise and amplitude-modulated signal. A new linear approximation approach is advanced to calculate the signal-to-noise ratio. In the linear approximation only the drift term is linearized, the multiplicative noise term is unchangeable. It is found that there appears not only the standard form of stochastic resonance but also the broad sense of stochastic resonance, especially stochastic multiresonance appears in the curve of signal-to-noise ratio as a function of coupling strength A between the real and imaginary parts of the pump noise.

NOISE IDENTIFICATION FOR HYDRAULIC AXIAL PISTON PUMP BASED ON ARTIFICIAL NEURAL NETWORKS

The noise identification model of the neural networks is established for the 63SCY14 IB hydraulic axial piston pump. Taking four kinds of different port plates as instances, the noise identification is successfully carried out for hydraulic axial piston pump based on experiments with the MATLAB and the toolbox of neural networks, The operating pressure, the flow rate of hydraulic axial piston pump, the temperature of hydraulic oil, and bulk modulus of hydraulic oil are the main parameters having influences on the noise of hydraulic axial piston pump. These four parameters are used as inputs of neural networks, and experimental data of the noise are used as outputs of neural networks, Error of noise identification is less than 1% after the neural networks have been trained. The results show that the noise identification of hydraulic axial piston pump is feasible and reliable by using artificial neural networks. The method of noise identification with neural networks is also creative one of noise theoretical research for hydraulic axial piston pump.

Numerical and experimental studies of hydraulic noise induced by surface dipole sources in a centrifugal pump

The influences of the four different surface dipole sources in a centrifugal pump on the acoustic calculating accuracy are studied in this paper, by using the CFD combined with the Lighthill acoustic analogy methods. Firstly, the unsteady flow in the pump is solved based on the large eddy simulation method and the pressure pulsations on the four different surfaces are obtained. The four surfaces include the volute surface, the discharge pipe surface, the inner surface of the pump cavity, and the interfaces between the impeller and the stationary parts as well as the outer surface of the impeller. Then, the software Sysnoise is employed to interpolate the pressure fluctuations onto the corresponding surfaces of the acoustic model. The Fast Fourier Transform with a Hanning window is used to analyze the pressure fluctuations and transform them into the surface dipole sources. The direct boundary element method is applied to calculate the noise radiated from the dipole sources. And the predicted sound pressure level is compared with the experimental data. The results show that the pressure fluctuations on the discharge pipe surface and the outer surface of the impeller have little effect on the acoustic simulation results. The pressure pulsations on the inner surface of the pump cavity play an important role in the internal flow and the acoustic simulation. The acoustic calculating error can be reduced by about 7% through considering the effect of the pump cavity. The sound pressure distributions show that the sound pressure level increases with the growing flow rate, with the largest magnitude at the tongue zone.