Abstract:

To alleviate the effects of aircraft noise effectively and choose the aircraft type which has lower noise, according to characteristics of a domestic airport noise monitoring data, this paper selected The Grey Relational Analysis of B-Mode that both has proximity and similarity to analyze the same flight with six kinds of aircraft’s noise monitoring data at the airport in a month. Moreover, according to the need of the research problem, it designed dimensionless processing method which optimized the noise monitoring data weight, improved The Grey Relational Analysis of B-Mode and calculated the each aircraft noise date and the optimal noise data’s correlation, then selected the needed low noise model. The results showed that the improved Grey Relational Analysis of B-Mode was suitable for the selection of low noise aircraft, and the analysis results were consistent with the actual, besides, the B733 models could mostly satisfy the conditions of low noise at the airport.

摘要：

为有效缓解飞机噪声的影响，选择出噪声值更小的机型，针对国内某机场噪声监测数据特点，选用兼具相近性与相似性的灰色 B型关联分析法对该机场一个月内同一航班六种机型噪声监测数据进行分析。根据研究问题需要，设计无量纲化处理方法，优化噪声监测数据权重，改进灰色 B型关联度方法，计算各机型噪声数据与最优数据的关联度，优选出满足条件的低噪声机型。结果表明，改进后灰色 B型关联度方法适用于低噪声飞机选型问题，分析结果符合实际，其中 B733机型最能满足该机场低噪声的条件。

关键词: 声学, 飞机选型, 灰色 B型关联度, 无量纲化, 机场噪声, 权重