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Active noise control in a stochastic domain based on a finite element model
... Then, if the noise level is low and is of broadband type, the value can be high, closer to upper limit of Eqn. (2). Whereas, if the noise level is high and is of narrowband type, has to be set low to assure convergence. ...
... Introducing a simulator at the input of signals recorded in the silenced object makes it possible to compare the effectiveness of the system. This is a direct method since the difference consists in substituting a real object with a simulator (see Airaksinen, Heikkola and Toivanen [8]). The entire process can thus be automated and carried out practically without a human. ...
At the end of the 20th century, a significant development in digital technologies of signal processing made it possible to apply active noise control methods in new domains. A proper selection of the reference signal source is a main problem in implementing such systems. This paper presents an estimation method based on an indicator of the coherent power level. It also presents a simple system of active noise control in a car, operating according to the proposed method of optimising the positioning of reference sources. This system makes it possible to considerably increase the comfort of work of drivers in various kinds of road transport without a great increase in cost. This is especially significant in the case of trucks and vans. Passive barriers are considerably more expensive in them, which results in a higher level of noise than in passenger cars.
The low-frequency broadband noise generated by an air-conditioning unit on a railway vehicle may be significant in situations where the vehicle is stopped or its speed is low. Low-frequency acoustic radiation is extremely difficult to attenuate using passive means, so in this work, active noise control (ANC) techniques were applied. Laboratory experiments were performed in which noise from two different sources, namely from loudspeakers and an axial fan, was introduced into a real air-conditioning duct, identical to that installed on a subway vehicle. The control approach used a doubled, single-input, single-output (SISO), feedforward, filtered-X LMS algorithm. Control algorithms were designed using the Matlab-Simulink program and the Real Time Windows Target toolbox of Matlab in order to run the ANC in real time. Attenuations of 15-20 dB at the error microphone locations were achieved when loudspeakers were used as primary noise generators. However, noise reduction was quite poor when noise was introduced via the axial fan. This was due to turbulence generated by the airflow, which has a negative influence on the performance of the control system. (C) 2003 Institute of Noise Control Engineering.
State-of-the-art finite-element methods for time-harmonic acoustics governed by the Helmholtz equation are reviewed. Four major current challenges in the field are specifically addressed: the effective treatment of acoustic scattering in unbounded domains, including local and nonlocal absorbing boundary conditions, infinite elements, and absorbing layers; numerical dispersion errors that arise in the approximation of short unresolved waves, polluting resolved scales, and requiring a large computational effort; efficient algebraic equation solving methods for the resulting complex-symmetric non-Hermitian matrix systems including sparse iterative and domain decomposition methods; and a posteriori error estimates for the Helmholtz operator required for adaptive methods. Mesh resolution to control phase error and bound dispersion or pollution errors measured in global norms for large wave numbers in finite-element methods are described. Stabilized, multiscale, and other wave-based discretization methods developed to reduce this error are reviewed. A review of finite-element methods for acoustic inverse problems and shape optimization is also given. © 2006 Acoustical Society of America.
We present an efficient method for the numerical realization of elliptic PDEs in domains depending on random variables. Domains
are bounded, and have finite fluctuations. The key feature is the combination of a fictitious domain approach and a polynomial
chaos expansion. The PDE is solved in a larger, fixed domain (the fictitious domain), with the original boundary condition
enforced via a Lagrange multiplier acting on a random manifold inside the new domain. A (generalized) Wiener expansion is
invoked to convert such a stochastic problem into a deterministic one, depending on an extra set of real variables (the stochastic
variables). Discretization is accomplished by standard mixed finite elements in the physical variables and a Galerkin projection
method with numerical integration (which coincides with a collocation scheme) in the stochastic variables. A stability and
convergence analysis of the method, as well as numerical results, are provided. The convergence is “spectral” in the polynomial
chaos order, in any subdomain which does not contain the random boundaries.
In this paper, we investigate the problem of finding the optimal location of sensors and actuators to achieve reduction of the noise field in an acoustic cavity. We offer two control strategies: the first is based on linear quadratic tracking where the offending noise is tracked, and the second considers the formulation of the harmonic control strategy as a periodic static output feedback control problem. The first method, which is based on full state information, is suitable for optimal location of actuators while the second strategy can extend the results to finding optimal location of sensors as well as actuators. For both methods we consider the optimization of an appropriate quadratic performance criterion with respect to the location of the actuators and/or the sensors. Numerical examples are presented to compare the effectiveness of each control strategy and also the effect of optimal placement of actuators and sensors.
The active control of sound is analyzed in the framework of the mathematical theory of optimal control. After setting the problem in the frequency domain, we deal with the state equation, which is a Helmholtz partial differential equation. We show existence of a unique solution and analyze a finite element approximation when the source term is a Dirac delta measure. Two optimization problems are successively considered. The first one concerns the choice of phases and amplitudes of the actuators to minimize the noise at the sensors location. The second one consists in determining the optimal actuators placement. Both problems are then numerically solved. Error estimates are settled and numerical results for some tests are reported. Key words. Dissipative acoustics, noise reduction, active control, optimal control problem, finite element approximation. AMS subject classifications. 49J20, 49K20, 65N15 1. Introduction. Noise
Active noise control (ANC) is achieved by introducing a cancelling
“antinoise” wave through an appropriate array of secondary
sources. These secondary sources are interconnected through an
electronic system using a specific signal processing algorithm for the
particular cancellation scheme. ANC has application to a wide variety of
problems in manufacturing, industrial operations, and consumer products.
The emphasis of this paper is on the practical aspects of ANC systems in
terms of adaptive signal processing and digital signal processing (DSP)
implementation for real-world applications. In this paper, the basic
adaptive algorithm for ANC is developed and analyzed based on
single-channel broad-band feedforward control. This algorithm is then
modified for narrow-band feedforward and adaptive feedback control. In
turn, these single-channel ANC algorithms are expanded to
multiple-channel cases. Various online secondary-path modeling
techniques and special adaptive algorithms, such as lattice,
frequency-domain, subband, and recursive-least-squares, are also
introduced. Applications of these techniques to actual problems are
highlighted by several examples
This paper describes a number of recent advances in the prediction of automotive interior noise. A brief review of existing modeling methods is given. Recent advances are then discussed in the following areas: (i) low frequency FE models, (ii) airborne SEA models, (iii) structure-borne SEA models and (iv) the use of CFD for source modeling.
An efficient constrained optimization-based prototype program OPTANC is developed to expedite the optimum design of active noise control systems in enclosures. The boundary element method is used to model the sound field of enclosures in which the walls provide complex impedance and point noise sources may exist at arbitrary locations. A sequential quadratic programming algorithm is selected as the optimizer for the deisgn because of its accuracy, efficiency, and reliability. The program is coded in C with portability on micro, mini, and mainframe computers, and is also modularized for future expansion. Simulations show that the software can effectively and efficiently produce the optimal locations and sound strengths of the control sources for active noise control problems.
The present work discusses waves and impedances, the determination of
sound power levels and directivity, outdoor sound propagation, sound in
small enclosures, noise in rooms, sound-absorbing materials and sound
absorbers, the interactions of sound waves with solid structures,
vibration isolation, and structural damping. Also discussed are
enclosures and wrappings, active noise control, damage-risk criteria for
hearing and human body vibration, criteria for noise and vibration in
communities, buildings, and vehicles, machinery noise prediction, noise
and vibration control for internal combustion engines, noise and
vibration of electrical machinery, and elements of gear noise
prediction. (No individual items are abstracted in this volume)
A physical damping is considered as a preconditioning technique for acoustic and elastic wave scattering. The earlier preconditioners for the Helmholtz equation are generalized for elastic materials and three-dimensional domains. An algebraic multigrid method is used in approximating the inverse of damped operators. Several numerical experiments demonstrate the behavior of the method in complicated two-dimensional and three-dimensional domains.
A preconditioner defined by an algebraic multigrid cycle for a damped Helmholtz operator is proposed for the Helmholtz equation. This approach is well-suited for acoustic scattering problems in complicated computational domains and with varying material properties. The spectral properties of the preconditioned systems and the convergence of the GMRES method are studied with linear, quadratic, and cubic finite element discretizations. Numerical experiments are performed with two-dimensional problems describing acoustic scattering in a cross section of a car cabin and in a layered medium. Asymptotically the number of iterations grows linearly with respect to the frequency while for lower frequencies the growth is milder. The proposed preconditioner is particularly effective for low-frequency and mid-frequency problems.
The principles of acoustic and vibroacoustic reciprocity are explained. Examples are then given of applications of acoustic
reciprocity to the experimental analysis of sound radiation by various systems of interest to noise control engineers. The
final part of the paper is devoted to a presentation of examples of the practical application of Lyamshev reciprocity to problems
of identifying and quantifying sources of noise that operate in a variety of engineering systems.
Numerical simulation has been used to predict the reduction of acoustic potential energy in a mobile mining vehicle cabin as a result of active noise control (ANC). Resonance frequencies and mode shapes of both the structural and cavity modes were calculated using a finite element (FE) model. Modal coupling analysis was used to determine the coupled response of the model to an interior acoustic source, and the results were compared to measurements taken inside the cabin. Correlation between the FE model and physical measurements was improved to the extent that the model could be used to predict the effect of ANC in the cabin for different configurations of control sources and error sensors. As expected from previous work, it was found that the acoustic potential energy inside the cabin could be significantly reduced if a control source is placed in close proximity to the primary volume velocity source. However, increasing the number of sensors and/or increasing the number of control sources located remotely from the primary source had little impact on the achievable reduction in the overall acoustic potential energy in the cabin. This supported results obtained in off-line experiments using control source to error sensor transfer function measurements and quadratic optimization theory, where it was found that good reduction at the error sensors was possible inside the mining vehicle cabin but that global control was not feasible using sources remotely located from the primary source.
Since the frequency and propagation characteristics of engine
exhaust noise are dependent on the engine rotational speed, an adaptive
noise control algorithm should have fast convergence features. An
effective active noise control (ANC) system based on the
lattice-structure adaptive filter is developed for the control of car
exhaust noise. The developed ANC system is implemented using a DSP and
applied to the active control of engine exhaust noise to show its
successful control
Ideas and methods for mod-eling 3D human ?gures
- M Bastioni
- S Re
- S Misra
M. Bastioni, S. Re, and S. Misra, Ideas and methods for mod-eling 3D human ?gures, in Proceedings of the 1st Bangalore Annual Compute Conference, ACM, 2008.
- P A Nelson
- S J Elliot
P. A. Nelson, S. J. Elliot, Active Control of Sound, Academic Press, London,
1999.