Sound quality evaluation of high-speed train interior noise by adaptive Moore loudness algorithm
基于自适应Moore响度算法研究高速列车车内声品质（英文）作者机构：Department of Energy Engineering Zhejiang University Hangzhou 310027 China
出 版 物：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 (浙江大学学报（英文版）A辑（应用物理与工程）)
年 卷 期：2017年第18卷第9期
页 面：690-703页
核心收录：
基 金：supported by the Fundamental Research Funds for the Central Universities(No.2016QNA4012) China
主 题：High-speed train Sound quality evaluation Equivalent rectangular bandwidth (ERB) spectrum Adaptive Mooreloudness algorithm (AMLA) Unusual random noise
摘 要：An online experiment to acquire the interior noise of a China Railways High-speed （CRH） train showed that it wasmainly composed of middle-low frequency components and could not be described properly by linear or A-weighted soundpressure level （SPL）. Thus, the appropriate way to evaluate the high-speed train interior noise is to use sound quality parameters,and the most important is loudness. To overcome the disadvantages of the existing loudness algorithms, a novel signal-adaptiveMoore loudness algorithm （AMLA） based on the equivalent rectangular bandwidth （ERB） spectrum was introduced. The valida-tion reveals that AMLA can obtain higher accuracy and efficiency, and the simulated dark red noise conforms best to thehigh-speed train interior noise by loudness and auditory assessment. The main loudness component of the interior noise is below27.6 ERB rate （erbr）, and the sound quality of the interior noise is relatively stable between 300-350 km/h. The specific loudnesscomponents among 12-15 erbr stay invariable throughout the acceleration or deceleration process while components among20-27 erbr are evidently speed related. The unusual random noise is effectively identified, which indicates that AMLA is anappropriate method for sound quality assessment of the high-speed train under both steady and transient conditions.
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