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OPTIMAL NOISE CONTROL ON PLANT USING SIMULATED ANNEALING

机译:模拟退火对植物的最佳噪声控制

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摘要

Noise control is important and essential in a manufacturing factory, where the noise level is restricted by the Occupational Safety and Health Act. Several researches on new techniques of single noise control have been well addressed and developed; however, the study of noise depression on the whole plant noise by using optimum allocation planning is hardly found. An improper machine allocation will not only result in the tremendous cost on noise control task, but also cause the harmful environment for the neighborhood; therefore, the approach of optimum and economic allocation of noise sources within a constrained plant area becomes crucial and obligatory. In this paper, a novel technique of simulated annealing (SA) is applied in the numerical optimization, and the multi-noise plant with various sound monitoring systems is also introduced. Before optimization, the single noise is tested and compared with the simulated data from SoundPlan, a commercial sound simulation package, for the accuracy check of the mathematical model. The result reveals to be within good agreements. The proposed SA optimization on the allocation of multi-noise plant surely provides an economic and effective methodology in reducing the sound accumulation around the plant boundary.
机译:噪声控制在制造工厂中是重要且必不可少的,在制造工厂中,噪声水平受到《职业安全与健康法》的限制。对单一噪声控制新技术的一些研究已经得到很好的解决和发展。但是,几乎没有发现采用最佳分配计划对整个工厂的噪声进行抑制的研究。机器配置不当,不仅会导致噪声控制任务的巨额成本,还会给附近居民带来有害的环境。因此,在受限的工厂区域内优化和经济分配噪声源的方法变得至关重要且必不可少。本文将一种新的模拟退火技术(SA)用于数值优化,并介绍了具有各种声音监控系统的多噪声工厂。在优化之前,先测试单个噪声,然后将其与来自商业声音模拟包SoundPlan的模拟数据进行比较,以检查数学模型的准确性。结果显示出良好的协议。拟议的多噪声植物分配的SA优化无疑为减少植物边界周围的声音积累提供了一种经济有效的方法。

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