基于SEA-PSA的地铁车内噪声顶层指标分解方法
刘舫泊1，张捷2，郭建强3，肖新标*,1
（1.西南交通大学 牵引动力国家重点实验室，四川 成都 610031；2. 四川大学 高分子材料工程国家重点实验室/高分子研究所，四川 成都 610065；3.中车青岛四方机车车辆股份有限公司，山东 青岛 266111）
摘要：地铁列车低噪声设计最基本和关键的第一步是为轨道车辆各主要部件分配声学指标，使其噪声性能满足低噪声设计目标限值，为此，本文提出一种基于SEA-PSA的地铁噪声顶层指标分解方法。首先，以一节地铁列车作为算例，基于统计能量分析（SEA）理论建立车内噪声模型并验证。然后，基于参数灵敏度分析理论，使用向前差分计算不同输入参数的灵敏度，包括通过空气路径传播的声源激励、通过结构路径传播的振源激励以及车体板件隔声，通过灵敏度分析法获得关键参数。得到关键输入参数后为其分配声学指标，制订声规范。结果表明：轮轨噪声和空调通风管道噪声及地板、侧墙、车窗的隔声是地铁列车运行时影响车内噪声的关键参数，为其分配声学指标可降低客室内声压级3 dB，满足限值要求。本文提出的基于SEA-PSA顶层指标分解方法是科学的、合理的，是实现车内低噪声设计的有效方法。
关键词：地铁；车内噪声；参数灵敏度分析；统计能量分析；仿真分析；噪声预测
中图分类号：TB533+.2 文献标志码：A doi：10.3969/j.issn.1006-0316.2021.08.004
文章编号：1006-0316 (2021) 08-0022-07
Subway Noise Top Level Index Decomposition Method Based on Parameter Sensitivity Analysis
LIU Fangbo1，ZHANG Jie2，GUO Jianqiang3，XIAO Xinbiao1
( 1.State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China;2.State Key Laboratory of Polymer Materials Engineering / Polymer Research Institute, Sichuan University, Chengdu 610065, China; 3.CRRC Qingdao Sifang Co., Ltd., Qingdao 266111, China )
Abstract: The most basic and critical first step in low noise design of subway trains is to assign acoustic indicators to the main components of the rail vehicles so that their noise performance meets the low noise design target limits. To this end, this paper proposes a SEA-PSA-based decomposition method for subway noise top-level indicators. This article uses a subway train as an example to illustrate this method. Firstly, an in-vehicle noise model was establish based on statistical energy analysis (SEA) theory and had been verified. Then, based on the parametric sensitivity analysis theory, the forward difference calculation method is used to study the sensitivity of different input parameters, including sound source excitation through air path propagation, vibration source excitation through structural path, and sound insulation of vehicle body panels. After key parameters were obtained, acoustic indicators were assigned to them and acoustic specifications were formulated. The results showed that the wheel-rail noise and noise of the air-conditioning ventilation ducts and the sound insulation of the floor, window and side walls were the key parameters affecting the interior noise of the subway train. Assigning acoustic indicators to it can reduce the sound pressure level in the guest room by 3dB, which meets the limit requirements. The SEA-PSA top-level index decomposition method proposed in this paper is scientific and reasonable, and it is an effective method to realize interior low-noise design.
Key words：metro；interior noise；parameter sensitivity analysis；statistical energy analysis；simulation analysis；noise prediction
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收稿日期：2021-02-05
基金项目：国家自然科学基金（U1934203）
作者简介：刘舫泊（1996－），男，江苏徐州人，硕士研究生，主要研究方向为轨道交通减振降噪，Email：liufangbo0112@163.com。*通信作者：肖新标（1978－），男，广东阳春人，博士，副研究员，博士生导师，主要研究方向为铁路噪声与振动，Email：xinbiaoxiao@163.com。
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