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Design Optimization of a Power Generator Soundproofing Enclosure

机译:发电机隔声罩的设计优化

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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.
机译:为了抑制往复式发动机型发电机的空气传播噪声,具有无源噪声控制外壳是至关重要的要求。这些外壳的设计需要在声压级和设计成本方面进行优化。我们已使用现有的声学方程式,基于针对声压级和外壳设计成本得出的目标函数获得了优化。诸如遗传算法和粒子群算法的元启发式优化算法能够解决这些优化问题,这些优化问题对不同的参数有约束。针对现实世界设计问题获得的结果证实,就解决方案的最优性和计算效率而言,粒子群优化比遗传算法提供了更好的结果。此外,据观察,在SPLE的首选范围内,最小外壳设计成本与外壳声压级(SPLE)之间存在显着的线性关系(R-Squared = 99.3%,p值<; 0.001)。值(65到70)。最小的外壳设计成本随着SPLE值的降低而线性增加。因此,最小可能的SPLE值取决于可用的财务资源。

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