Paper
30 March 2006 Optimization of actuator and sensor positions for an active noise reduction system
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Abstract
Different systems and strategies have been invented in order to reduce the noise level inside the fuselage of aircrafts. First of all passive methods like adding materials with high damping or vibration absorbing qualities were used. Due to mass reduction as a major aspect in aircraft design a lot of research is focused on active noise reduction (ANR). The level of attenuation gained by an ANR - system is depending on several attributes of the system like hardware and software in use. Another important parameter, which has a great impact on the performance, is the positioning of the actuators and sensors. Because of the high number of possible arrangements of actuators and sensors in three dimensional spaces, it is almost impossible to determine the optimal positions by experimental work. Therefore numerical optimization is applied. In this paper a hybrid evolutionary algorithm is introduced for the calculation of appropriate configurations for a fixed number of actuator and sensors out of a high number of possible positions for an ANR - system within a military aircraft. The presented COSA - algorithm (cooperative simulated annealing) connects qualities of two well known optimization algorithms, the simulated annealing (SA) and genetic algorithm (GA). A general description of the algorithm and the acoustical basics will be provided together with an overview of the results.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sten Böhme, Delf Sachau, and Harald Breitbach "Optimization of actuator and sensor positions for an active noise reduction system", Proc. SPIE 6171, Smart Structures and Materials 2006: Industrial and Commercial Applications of Smart Structures Technologies, 61710N (30 March 2006); https://doi.org/10.1117/12.658418
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Cited by 5 scholarly publications.
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KEYWORDS
Actuators

Sensors

Ear

Evolutionary algorithms

Binary data

Algorithms

Denoising

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