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Journal ArticleDOI

Active control of turbulent boundary layer-induced sound transmission through the cavity-backed double panels

26 May 2018-Journal of Sound and Vibration (Academic Press)-Vol. 422, pp 161-188
TL;DR: In this article, the authors present a theoretical study of active control of turbulent boundary layer TBL induced sound transmission through the cavity-backed double panels, where a feedback control unit is located inside the acoustic cavity between the two panels.
About: This article is published in Journal of Sound and Vibration.The article was published on 2018-05-26 and is currently open access. It has received 22 citations till now. The article focuses on the topics: Sound transmission class & Sound pressure.

Summary (4 min read)

1. Introduction

  • In high speed automotive, aerospace, and railway transportation, the turbulent boundary layer (TBL) is one of the most important sources of interior noise.
  • Consequently the trim panels radiate sound into the vehicle interior.
  • Between the different models developed over the years to describe the wall pressure fluctuations due to a TBL [3], the Corcos model is among the simplest [4, 5].
  • The passive sound transmission control is ineffective in the lowfrequency range since the passive sound absorptive materials can not attenuate the large-length waves.
  • Feedback control systems can be used instead, and some promising results have been reported in the last decade [14, 20, 21, 22].

2. The model problem

  • The analytical model outlined in this section is used to predict the noise transmission through an acoustically coupled double panel system into a rectangular cavity when an active vibration isolation unit is used.
  • The problem under analysis is physically given by the interaction of an aerodynamic model, that represents the TBL pressure fluctuations on the structure, and a structural-acoustic model, that gives the noise transmission and interior sound levels.

2.1. Aerodynamic model

  • The wall pressure field, generated by a fully developed TBL with zero mean pressure gradient, can be regarded as homogeneous in space and stationary in time [3, 28].
  • It is thus possible that the results presented in the paper qualitatively differ for different convective speeds and the dimensions of the panels.
  • In the following sections the properties of the physical system used are defined in detail.
  • The longitudinal and lateral decay rates of the coherences, αx and αy respectively, are normally chosen to yield good agreement with experiments.

2.2. Structural-acoustic model

  • The model encompasses a cavitybacked homogeneous double panel driven on one side by a stationary TBL.
  • Real sensor-actuator transducers would certainly exhibit more complex highfrequency behaviour and decrease stability margins of the active control systems considered in the study.
  • In the following section, the structural-acoustic model presented describes the interaction between the vibrating structure and the turbulent flow assuming a one-way interaction, i.e. the influence of the panel vibration on the boundary layer is neglected [33].
  • In Eq. (8)-(9), v represents the distribution of source volume velocity per unit volume (including the effect of the boundary surface vibration), c0, ρ0 and σac are the sound speed in air, mean density of air and acoustic damping ratio for both cavities, respectively.

3.1. Description of the simplified model

  • The stability and performance analysis of the active control system are carried out using a simplified model.
  • Note that the first mode of each air cavity is characterised by a uniform pressure variation throughout the cavity volume and by a zero natural frequency.
  • The resulting coupled system 9 then behaves exactly as a two degree of freedom (DOF) mechanical system which, as shown in Fig. 2, is represented through mass and stiffness parameters m1,m2, k1, k2, k3, and which is characterised by two coupled mode shapes and two natural frequencies.
  • The remaining geometrical and physical properties used throughout the paper are shown in Table 1.

3.2. Stability

  • A system is stable if all roots of its characteristic equation have negative real parts.
  • Additionally, all the principal diagonal minors ∆i of the Hurwitz matrix must be positive.
  • It can be stated that in the case with β < 1 the source body, having the larger uncoupled natural frequency than the radiating body, behaves more like a fixed reference base against which the actuator can react without pronounced feedthrough effect that could otherwise compromise stability properties.
  • The frequency response function between the reaction force component and the velocity sensor is thus responsible for the stability problems in case β >.
  • This is because frequency response functions between two different points of a flexible structure do not necessarily have their phases bound within a 180 degree range, whereas the driving point FRFs do have their phase limited within a 180 degrees range.

3.3. Performance

  • The performance of the active control system is analysed by using two different load conditions.
  • Firstly, a white noise forcing is assumed on m1, Fig. 2, where the mass m1 represents the source panel and is thus referred to as the source body.
  • Then, the mean squared velocity of the mass m2 is found by calculating the integral over all frequencies of the squared magnitude of the transfer mobility, Eq. (28), of the system in Fig.
  • Note that the mean squared displacement of the mass m2 is proportional to the mean squared pressure in the cavity c2 according to the two mode assumption, see Eq. (29).
  • The frequency- and space-averaged velocity PSD of the radiating panel is used.

3.3.1. Point force excitation

  • The mean squared velocity of the radiating body is plotted as function of the passive and active damping ratio in Fig.
  • This is however only due to a) the limitations of the reduced order model and its inability to capture the high-frequency behaviour of the double panel structure, and b) the fact that idealised sensor and actuator transducers are assumed.
  • The passive damping ratio is again set to the optimal value that lies on the white dash-dotted line in Fig.
  • In addition, the roll-off at higher dimensionless frequencies, above approximately 2.1, is compromised as shown in Fig. 5-a.
  • In conclusion, the inconsistent impact of the passive damping ratio at various frequency ranges is the reason why the frequency averaged kinetic energy of the radiating panel plotted in Fig. 6-a has a minimum which corresponds to the optimal passive damping coefficient ηopt.

3.3.2. Turbulent boundary layer excitation

  • The performance of the control system in reducing the TBL−induced sound transmission is studied by using the simplified, reduced order model.
  • As with the point force excitation, the radiating panel kinetic energy decreases monotonically with ξ when β < 1 Fig. 7-(b) and Fig. 8-(b).
  • By comparing the situation with the TBL excitation to the scenario with the white noise force excitation discussed in the previous subsection, it can be stated that the stochastic TBL pressure distribution results in a steeper high frequency roll-off of the velocity PSD, shown in Fig.
  • This requires careful tuning of the passive and active damping ratios to the optimum combination.

4. Results with the full order model

  • The stability and performance of the active control system are again discussed in terms of the mean squared vibration velocity of the radiating panel and the mean squared acoustic pressure in the cavity c2.
  • The number of modes used enables accurate calculation of the mean squared pressure and velocity up to 1000 Hz.
  • Two load conditions are analysed: 1) white noise point force excitation; and 2) TBL excitation.
  • The large number of modes precludes the use of the Routh-Hurwitz criterion to assess the stability of the active system such that the Nyquist criterion is used instead.

4.1. Stability

  • The sensor-actuator OL − FRF can be used to analyse the stability of the closed loop control system by using the Nyquist criterion.
  • In Fig. 11 - 12, the corresponding Bode and Nyquist plots are shown.
  • Thus the system with β < 1 is unconditionally stable under the assumption of ideal sensor-actuator frequency response.
  • Regarding the high-frequency behaviour, it is still interesting that the phase of the OL − FRF is bound between ±90 degrees, given the fact that the sensor and the actuator are not dual and collocated.
  • Therefore the relative importance of the non-collocated FRF decreases as the frequency increases.

4.2. Performance

  • In the following subsection, the performance of the control system assuming a full order model is analysed for both load conditions: point force and TBL.
  • The frequency-averaged vibration velocity of the radiating panel and the sound pressure in the acoustic enclosure c2 are used as the metrics for the quality of the sound transmission control.

4.2.1. Point force excitation

  • In the case of a point force excitation on the radiating panel, the mean squared velocity at the centre of the radiating panel and the mean squared acoustic pressure near the corner of 24 the cavity c2 are calculated using the procedure described in Section 2.2.
  • The squared magnitude of either frequency response function is integrated numerically over the frequency range 0 − 1000 Hz.
  • The amplitude of the velocity at the centre of the radiating panel per unit excitation force on the source panel is shown in Fig. 14-b, and the amplitude of the sound pressure per unit excitation force at the pressure monitoring point in the cavity c2 is shown in Fig. 15-b.
  • Again, the results with the active approach are contrasted to the results using a fully passive approach.

4.2.2. Turbulent boundary layer excitation

  • For the full order model assuming the TBL excitation on the source panel, the performance of the control system is analysed in terms of: a) the velocity PSD at the centre of the radiating panel, pr, and b) the pressure PSD near the corner of the cavity c2, see Fig.
  • The pressure PSD near the corner of c2 is plotted versus frequency in Fig. 17-b with β < 1 and Fig. 19-b with β > 1 for three cases: without control, with passive control using cp only, and finally with active control using both cp and g.
  • By comparing the right-hand side plot of Fig. 16 to the right hand side plot of Fig. 17, it can be concluded that large contributions to the interior sound pressure are due to the two lowest double panel modes.
  • Additional mode shapes obtained using the full order model are shown and discussed.

5. Conclusions

  • The active control of TBL noise transmission through a cavity-backed double panel is investigated.
  • Stability and performance of the velocity feedback active control system are carried out for a reduced order model and an increased order model.
  • The theoretical analysis indicates that the first fundamental mode and the mass-air-mass mode of the coupled system are the strongest radiators of sound into the back cavity.
  • Closed form expressions for these stability limits are given in terms of the minimal/maximal active damping ratio.
  • The fundamental resonance frequency of the source panel is larger than the fundamental resonance frequency of the radiating panel, which results in unconditionally stable control systems such that very large feedback gains can be used.

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References
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TL;DR: Improved convergence rate and stability are obtained by using an inner-outer factorization of the transfer path between the actuators and the error sensors, combined with a delay compensation technique using double control filters and a regularization technique that preserves the factorization properties.
Abstract: In this paper, real-time results are given for broadband multichannel active noise control using the regularized modified filtered-error algorithm. As compared to the standard filtered-error algorithm, the improved convergence rate and stability of the algorithm are obtained by using an inner–outer factorization of the transfer path between the actuators and the error sensors, combined with a delay compensation technique using double control filters and a regularization technique that preserves the factorization properties. The latter techniques allow the use of relatively simple and efficient adaptation schemes in which filtering of the reference signals is unnecessary. Results are given for a multichannel adaptive feedback implementation based on the internal model control principle. In feedforward systems based on this algorithm, colored reference signals may lead to reduced convergence rates. An adaptive extension based on the use of affine projections is presented, for which real-time results and simulations are given, showing the improved convergence rates of the regularized modified filtered-error algorithm for colored reference signals.

28 citations

Journal ArticleDOI
TL;DR: In this paper, an active damping method using Inertial Actuators (IAs) is considered and closed form expressions for the H2 optimal control parameters that minimise the kinetic energy of the primary structure are derived.

27 citations


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Journal ArticleDOI
TL;DR: In this article, the authors present a theoretical study of active vibration isolation on a two degree of freedom system, which consists of two lumped masses connected by a coupling spring and both masses are also attached to a firm reference base by a mounting spring.

25 citations


"Active control of turbulent boundar..." refers background in this paper

  • ...2 when excited by a point force and the one of a known two degree of freedom lumped parameter mechanical system [24]....

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  • ...In this context, some very effective feedback control methods have been proposed for vibration isolation [23, 24, 25]....

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  • ...The underlying reason for this is that in such situations, where the stability of the system is compromised, it would be better to place the sensor on the source panel and implement a direct source panel velocity feedback [24]....

    [...]

  • ...have been typically considered in the situations where the mechanical systems at hand can be accurately represented through their lumped parameter approximation [23, 24, 25]....

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TL;DR: In this article, a complete analytical model framework able to accurately predict the flow-induced noise in the interior of a transport vehicle cabin is presented, which can be used for the prediction of flowinduced noise for different types of transport vehicles, by changing some of the parameters.
Abstract: In this study, a complete analytical model framework able to accurately predict the flow-induced noise in the interior of a transport vehicle cabin is presented. The mathematical model framework presented represents a coupled structural-acoustic system, consisted by a plate subjected to a random excitation or to flow-induced noise, and an acoustic enclosure representing the transport vehicle cabin. The coupled analytical model is developed using the contribution of both structural and acoustic natural modes. It is shown that the analytical framework can be used for the prediction of flow-induced noise for different types of transport vehicles, by changing some of the parameters, as shown by the good agreement between the analytical results and several experimental studies. The results indicate that the analytical model is sensitive to the measurement location, with the change in position significantly affecting the predicted interior noise levels, as should be expected. Different sizes for the acoustic enclosure, as well as different types of panels were investigated. This study demonstrates the importance of including the acoustic receiving room (i.e., the vehicle cabin) contribution in the analytical formulation, in order to accurately predict the noise transmission and interior noise levels.

24 citations


"Active control of turbulent boundar..." refers background or methods in this paper

  • ...In order to model the structural-acoustic control problem at hand, the two panel displacements and the two acoustic enclosure pressures are calculated by coupling the wave equations for the two cavities with the governing equations for the two panels [35, 36]....

    [...]

  • ...(13), the constant Anx , Any and Anz are equal to √ 2 when nx , 0, ny , 0, nz , 0 respectively, and, they are equal to 1 when nx = 0, ny = 0 and nz = 0, respectively [36]....

    [...]

  • ...5) are found by solving the integrals over the plate area, as shown in [36]....

    [...]

  • ...(14) is expressed in the frequency domain, as [36]: Y (ω) = H (ω) X (ω) , (18) where...

    [...]

  • ...Since the TBL excitation is defined in terms of the power spectral density (PSD) of the wall pressure, it is convenient to write the coupled system governing equations in the PSD domain, SYY (ω) = H∗ (ω) SXX (ω) HT (ω) , (23) where SXX (ω) is the PSD matrix of the random excitation, which includes the PSD matrix of the TBL pressure; SYY (ω) is the PSD matrix of the plate displacements, SWWi (ω), and the acoustic pressures, SPPc (ω), and the superscripts ∗ and T denote Hermitian and matrix transpose, respectively [36]....

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Journal ArticleDOI
TL;DR: In this article, an active damping method using blended velocity feedback for the reduction of sound transmission through a simplified aircraft double panel is considered, which consists of a source and a radiating panel, which are coupled acoustically by the air in the cavity between them and structurally by four elastic mounts.
Abstract: In this paper an active damping method using blended velocity feedback for the reduction of sound transmission through a simplified aircraft double panel is considered. The double panel consists of a source and a radiating panel, which are coupled acoustically by the air in the cavity between them and structurally by four elastic mounts. The double panel is equipped with an array of nine voice-coil actuators that can react against the two panels. A velocity sensor is mounted at both panel junctions of each actuator. The outputs from the sensors on the source and radiating panels are weighted by factors α and 1 - α, respectively. The two weighted signals are then subtracted and combined into the error signal fed back to the actuator via a constant amplification gain. The stability and performance of such a decentralized velocity feedback system are analyzed experimentally as a function of the weighting factor α. Reductions between -10 and -18 dB in the radiated sound power have been measured at low-frequency resonances of the double panel, depending on the weighting factor implemented.

16 citations


"Active control of turbulent boundar..." refers result in this paper

  • ...Feedback control systems can be used instead, and some promising results have been reported in the last decade [14, 20, 21, 22]....

    [...]