<title>Study of shell interior noise control</title>

Abstract

There is a growing interest in the application of smart materials technology to the aircraft interior noise control problem. Some outstanding issues with the interior noise control problem include development of sensory systems that can lead to global sound level reduction in the cabin, and the safety concern of structural actuators used to reduce noise radiation. This paper presents two comparative studies: 1) comparison of several sensor configurations by using acoustic microphones, and 2) comparison of strain fields induced by discrete and distributed structural actuators. A uniform cylindrical shell is used as a simplified model of a section of fuselage. Extensive simulations have been conducted. Major findings of this paper are 1 . In order to control the interior noise in the shell where there is no acoustic source inside, one only needs to place acoustic sensors near the wall. Furthermore, if one uses the energy density as an error signal, one can reduce the number of error input channels substantially. In terms of the ability to lead to the global noise reduction, a 4-channel energy density sensor is found to be comparable to 32 microphones uniformly spaced on a ring.2. Distributed piezoelectric actuators tend to introduce smoother strain fields on the shell than discrete actuators as measured by a strain index defined in the paper. This quantitative result agrees with one' s intuition.Simulation results of adaptive control of multi-tone noise field using discrete and distributed structural actuators are also presented in the paper.

Active control of energy density in a one-dimensional waveguide: A cautionary note (L)

“…[10][11][12][13][14][15][16][17][18][19] Acoustic energy density, defined as the sum of the acoustic potential and kinetic energy densities at a point, is commonly estimated using the two-microphone method 1 and is given by ͑see the Appendix͒…”

Expression for the estimation of time-averaged acoustic energy density using the two-microphone method (L)

“…Subsequently, several authors have found energy density to be an effective sensor for active noise control applications, as it measures the total energy at a point, and generally outperforms microphones. [2][3][4][5][6] In the past, estimation of acoustic energy density has been made using one of two methods: time domain experiments or noise-free frequency domain simulations. The time domain method involves the use of additional electronics ͑either analog or digital͒ to calculate the pressure average and the particle velocity between the two sensing elements.…”

Statistical errors in the estimation of time-averaged acoustic energy density using the two-microphone method

“…Subsequently, several authors have found energy density to be an effective sensor for active noise control applications, as it measures the total energy at a point, and generally outperforms microphones. [2][3][4][5][6] The bias errors arising from the inherent and instrumentation errors in energy density sensing have been thoroughly investigated. [7][8][9] Additionally, the estimation of potential energy density and kinetic energy density in the frequency domain and the associated statistical errors have been discussed by Elko.…”