Abstract:
It is a vital requirement to have passive noise control
enclosure in order to depress air borne noise of reciprocating
engine type power generators. The design of these enclosures
needs to be optimized in terms of the sound pressure level
and the designing cost. We have used the existing acoustic
equations to obtain the optimization based on the objective
functions derived for the sound pressure level and enclosure design
cost. Metaheuristic optimization algorithms such as genetic
algorithms and particle swarm algorithm are capable of solving
these optimization problems which have constraints for different
parameters. The results obtained for a real world design problem
confirms that particle swarm optimization provides better results
than genetic algorithm in terms of optimality of the solutions and
also the computational efficiency. Furthermore, it was observed
that there is a significant linear relationship (R-Squared = 99.3%,
p-value < 0.001) between the minimum enclosure design cost
and the sound pressure level of the enclosure (SPLE) for the
preferred range for SPLE values (65 to 70). The minimum
possible enclosure design cost increases linearly with decreasing
SPLE value. Therefore, the least possible SPLE value depends
on the available financial resources.
Citation:
De Zoysa, A.D.N., Iroshan, K.A., Premaratne, U.K., & Ehelepola, I. (2018). Design optimization of a power generator soundproofing enclosure. In R. Samarasinghe & S. Abeygunawardana (Eds.), Proceedings of 2nd International Conference on Electrical Engineering 2018 (pp. 21-25). Institute of Electrical and Electronics Engineers, Inc. https://ieeexplore.ieee.org/xpl/conhome/8528200/proceeding