Design optimization of a power generator soundproofing enclosure

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.