scholarly journals Auditory sustained field responses to periodic noise

2012 ◽  
Vol 13 (1) ◽  
Author(s):  
Sumru Keceli ◽  
Koji Inui ◽  
Hidehiko Okamoto ◽  
Naofumi Otsuru ◽  
Ryusuke Kakigi
Author(s):  
Peiman Naseradinmousavi

In this paper, we focus on a novel nonlinear modeling and dynamic analysis of the actuated butterfly valves coupled in series. The actuated valves used in the chilled water systems of the U.S. Navy and commercial ships, namely, “smart valves,” recently have received much attention when many of them are operating in a complex network. The network regulates the pressure of the pipeline, while several nonlinear torques/forces including the hydrodynamic and bearing torques and the magnetomotive force affect the performance of each set individually and subsequently the whole system via the couplings among the valves. The contribution of this work is to model such couplings in the presence of the nonlinearities and an applied periodic noise and then carry out dynamic analysis of the valves. We examine the model developed with/without actuation by applying a periodic noise on the upstream valve to capture the couplings among the parameters of both the actuators and valves. This would help us predict the behavior of a particular valve in the network subject to motions of other valves.


1996 ◽  
Vol 100 (4) ◽  
pp. 2780-2780 ◽  
Author(s):  
Nobuyuki Seguchi ◽  
Yasuyuki Shimada ◽  
Yoshitaka Nishimura ◽  
Tsuyoshi Usagawa ◽  
Masanao Ebata

1985 ◽  
Vol 150 (12) ◽  
pp. 666-669
Author(s):  
G. Jean Kant ◽  
Ron Smith ◽  
Leigh Landman-Roberts ◽  
Lysaida Cardenales-Ortiz ◽  
Edward H. Mougey
Keyword(s):  

2013 ◽  
Vol 318 ◽  
pp. 27-32
Author(s):  
Hao Cheng Wu ◽  
Yong Shou Dai ◽  
Wei Feng Sun ◽  
Li Gang Li ◽  
Ya Nan Zhang

Periodic noise is an important manifestation of the drill string vibration signal noise. In order to extract the characteristics of the signals which reflect the situation of the tools in drilling, the periodic components which influence the original drill string vibration signal in the well field were researched and the independent component analysis algorithm which is on the basis of negative entropy for periodic vibration noise separation was adopted. At the same time, the effect of algorithm demixing was improved where periodic noise components which existed in three directions of drill string vibration signals were used, combining with the improved particle swarm optimization algorithm to seek the optimal mixed matrix by which the multi-channel mixed-signal of independent component analysis algorithm could be structured. This method in operation was fast. And after separation each signal was of high similarity. Through the experimental simulation, the method was proven effective in the drill string vibration periodic noise signal separation.


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