Abstract
Active structural acoustic control (ASAC) is an effective method of reducing the sound radiation from vibrating structures. In order to implement ASAC systems using only structural actuators and sensors, it is necessary to employ a model of the sound radiation from the structure. Such models have been presented in the literature for simple structures, such as baffled rectangular plates, and methods of determining the radiation modes of more complex practical structures using experimental data have also been explored. A similar problem arises in the context of active noise control, where cancellation of a disturbance is required at positions in space where it is not possible to locate a physical error microphone. In this case the signals at the cancellation points can be estimated from the outputs of remotely located measurement sensors using the “remote microphone method”. This remote microphone method is extended here to the ASAC problem, in which the pressures at a number of microphone locations must be estimated from measurements on the structure of the radiating system. The control and estimation strategies are described and the performance is assessed for a typical structural radiation problem.
Highlights
Active vibration control has significant benefits compared to passive vibration control when there are size and weight restrictions on the control treatment
This can be difficult to implement for complex structures away from resonances and, in this paper an alternative Active structural acoustic control (ASAC) strategy has been proposed based on the remote microphone method previously employed in active noise control systems
The optimal solution for the ASAC algorithm based on the remote microphone method has first been derived and an iterative, steepest-descent based implementation has been presented
Summary
Active vibration control has significant benefits compared to passive vibration control when there are size and weight restrictions on the control treatment. These benefits become useful at lower frequencies where achieving high performance with passive noise control methods is often impractical due to its necessary size and weight [1] Another advantage of active control methods is the ability to more flexibly manipulate the sound or vibration response. If the matrix GHs Gs is positive-definite, which is generally the case in practice when Ls > M , the vector of control signals which minimises the cost function Js is given by setting the derivative of (3) with respect to the real and imaginary parts of u to zero [13].
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