209. Effects of Diameter on Active Control of Random Noise in Circular Ducts

2006 ◽  
Author(s):  
J. Slagley ◽  
S. Guffey
Keyword(s):  
2008 ◽  
Vol 123 (4) ◽  
pp. 1838-1841 ◽  
Author(s):  
Janatul I. Mohammad ◽  
Stephen J. Elliott ◽  
Andy Mackay
Keyword(s):  

2000 ◽  
Vol 19 (1) ◽  
pp. 35-46 ◽  
Author(s):  
Xiaojun Qiu ◽  
Colin H. Hansen

The filtered-x LMS algorithm (FXLMS) has been successfully applied to the active control of periodic and random noise and vibration. This paper presents a modified algorithm for active control of periodic noise based on the FXLMS algorithm which uses random noise for on-line cancellation path transfer function (CPTF) estimation. In the proposed algorithm, another two short adaptive filters are introduced. One is an adaptive noise cancellation filter, which is used to improve the convergence speed of the CPTF modelling filter in the presence of very large amplitude primary noise by cancelling the component of the error signal that is correlated with the primary noise. The other is an adaptive estimator, which is used to re-estimate the obtained CPTF (long FIR filter estimated by random noise) with a short FIR filter by using the periodic reference signal as the input. The traditional FXLMS algorithm is then used with the shortened FIR filter to filter the reference signal, thus providing significant processing flexibility in practical situations where the primary path transfer function changes much faster than the CPTF. Simulation results demonstrate the effectiveness of the proposed algorithm.


1986 ◽  
Vol 5 (4) ◽  
pp. 127-136
Author(s):  
R.F. La Fontaine ◽  
A. Cabelli ◽  
I.C. Shepherd

In situations involving turbulent, corrosive or high temperature exhaust gas, active control of duct-borne random noise might be more conveniently applied beyond the duct outlet. Near field attenuators are examined to disclose those configurations which radiate least noise to the far field, since it is usually there that the most serious complaints originate. Theoretical investigations of simple dipole, tripole and quadrupole source arrangements reveal that near field systems may prove applicable where the wave number kd (d- outlet diameter), is less than 0.73.


Author(s):  
P. Shashikala ◽  
V. Shankar ◽  
B. V. Nagaraja ◽  
R. Balasubramaniam ◽  
J. Harikrishnan

Abstract Adaptive feed forward control of structure based on ‘filtered -x’ LMS algorithm has been brought out for the active control of vibration in a typical CFRP beam structure. Initially the conventional filtered-x LMS control configuration and offline system identification method using DSP is discussed. Also the on-line system identification and control by additive random noise technique has been brought out. FIR filters are used for both system identification and control. Recent advances in electronics, high-speed digital signal processors have made active systems realizable, effective and inexpensive. Hence the active control method has been used to investigate a typical composite CFRP beam structure bonded externally with PZT actuators/sensors. At present vibration reduction of the order of 3db has been achieved.


Author(s):  
Sidnei Paciornik ◽  
Roar Kilaas ◽  
Ulrich Dahmen ◽  
Michael Adrian O'Keefe

High resolution electron microscopy (HREM) is a primary tool for studying the atomic structure of defects in crystals. However, the quantitative analysis of defect structures is often seriously limited by specimen noise due to contamination or oxide layers on the surfaces of a thin foil.For simple monatomic structures such as fcc or bcc metals observed in directions where the crystal projects into well-separated atomic columns, HREM image interpretation is relatively simple: under weak phase object, Scherzer imaging conditions, each atomic column is imaged as a black dot. Variations in intensity and position of individual image dots can be due to variations in composition or location of atomic columns. Unfortunately, both types of variation may also arise from random noise superimposed on the periodic image due to an amorphous oxide or contamination film on the surfaces of the thin foil. For example, image simulations have shown that a layer of amorphous oxide (random noise) on the surfaces of a thin foil of perfect crystalline Si can lead to significant shifts in image intensities and centroid positions for individual atomic columns.


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