In situ body mount optimization: theory and experiment

In this paper, an in situ method has been used to find the optimum set of body mounts for a given vehicle. The strength of this method is that it does not require the vehicle to be disassembled. Standard noise, vibration and harshness testing procedures are used to obtain frequency response function (FRF) models of the vehicle's subsystems. This is followed by FRF-based substructuring synthesis approach to obtain the overall vehicle model. The model is incorporated into an optimization algorithm to predict the optimum set of body mounts for a desired objective function. The in situ method is presented and applied to an experimental case study of a pick up truck. The experimental results confirmed the validity and effectiveness of this approach in finding the optimum body mount set, resulting in significant reduction in the vibration level of the vehicle.     

Human body modelling for traffic accident analysis

A traffic accident is a complex phenomenon with vehicles and human beings involved. During a collision, the vehicle occupant is exposed to substantial loads, which can cause the occupant injuries that depend on the level of passive safety, as well as on the occupant's individual characteristics. Correct estimation of injury severity demands a validated human body model and known impact conditions. A human body modelling procedure for the purpose of accident analysis is introduced. The occupant body has been modelled as a multibody system with rigid body segments connected. Geometrical and inertial properties of individual body segments were estimated using computed tomography. Frontal impact conditions were simulated on a sled test facility, while the human body dynamic response was measured. Comparison of experimental data and computer simulation revealed an influence of joint resistive properties on the occupant motion in collisions. The difference between measured and simulated response was minimised using optimisation method. Individualised human body modelling procedure enabled better prediction of the occupant motion during vehicle collision and thus more precise estimation of possible injuries in real-life traffic accidents.     

一种适用于复杂城市路网的浮动车实时地图匹配技术

地图匹配技术是浮动车系统从数据接收到结果展示各个环节中最为关键的一项内容,但是目前国际上浮动车系统多用于路网结构简单的高速公路系统,而将匹配技术应用于立交遍布、主辅路交错的复杂城市道路系统时往往得不到满意的匹配效果.文章通过对现有各种地图匹配方法的分析比较,针对大采集时间间隔GPS数据在北京市复杂路网结构中遇到的实际问题,提出了一种局部节点匹配的改进的最优路径选择算法,将该算法应用于实验系统后,获得了令人满意的匹配速度与准确度,证实了这一地图匹配算法能较好地适用于现代复杂城市路网的实时浮动车计算系统.     

轮胎噪音的噪音特性研究

为了从路面与车轮接触方面研究如何降低交通噪音,文章从声学基础概念入手,结合人耳听觉特性,从现场测量和实验室测量两方面对轮胎噪音的声学特性进行了分析,最后得出低噪音路面设计中几个重要指标的建议取值。     

摩托车发动机噪声试验研究

在摩托车发动机的噪声控制研究中,运用声功率、声强等高线图及频谱分析方法,对表面辐射噪声进行了声源识别和研究,进、排气噪声对测量面的声贡献较大;运用分别运行法进行噪声分离试验,将燃烧噪声、活塞敲击噪声、配气机构噪声、初级齿轮副啮合噪声分离,进一步分析了2种转速下该发动机的噪声组成和不同噪声的频谱特征,为降低该型发动机的表面辐射噪声奠定了基础。     

基于运营状态监测数据识别过桥车辆荷载

基于桥梁运营状态监测得到的应变历程数据,通过对测点影响线形状的较深入分析,建立了识别过桥车辆荷载的一种BWIM方法———“单峰锐度法”。结合实例的分析表明该方法能够较精确识别稀疏交通状态下车辆数量、大小、作用位置,并能推求影响线内多车作用下的荷载。     

车内自适应有源消声系统次级声源布放试验

在构建车内双次级声源有源消声系统的基础上,对系统中次级声源的布放进行了试验研究,分析了双次级声源的布放、次级声源与误差传声器的相对位置对车内消声区域和消声效果的影响,确定了次级声源和误差传声器的合理布放方案。研究表明,当误差传声器与次级声源的数目相同、误差传声器位于次级扬声器的中心线上,且与次级声源相距200 mm左右时消声效果最好。讨论了不同车型车内次级声源和误差传声器布置的可行性,给出了客车、货车和轿车车内次级声源和误差传声器布放的合理方案,可为多次级声源车内有源消声系统的设计提供参考。     

大跨径连续梁桥施工预拱度预测

建立预应力混凝土连续梁桥施工预拱度控制的BP神经网络模型，根据施工过程中桥面实测标高与设计值的差异，用BP神经网络识别预应力损失等参数，预测后续节段的预拱度。在湖北襄樊汉江四桥的施工控制中的应用表明该方法是有效的，与实测的结果较吻合。     

基于振动与静载试验的桥梁结构损伤识别法

以桥梁结构有限元为工具，把当前结构模型中各单元的等效面积、惯性矩以及板壳单元的厚度作为识别参数|p|，建立识别参数对于各种量测的灵敏度矩阵[S|p|]。同时以测取的结构某些部位的位移、应变以及低阶的振动模态参数为基准，与原先结构的分析结果进行比较建立综合误差向量{△E}。通过优化方法不断调整当前计算模型的参数{△P}使结构响应与相应的试验值最大程度地吻合({△E}小到一定量级)，从而得到结构参数变化的信息。以此为基础即可实现桥梁结构的损伤判别以及承载能力的评估。     

环境激励下桥梁结构模态识别与损伤检测的新方法

已有的环境激励下模态参数识别的方法对模态频率的识别精度相对较高,而对位移模态的识别则误差较大。本文提出一种利用移动质量块在不同位置时对桥梁的模态频率进行多次测量,用各次测得的频率值确定位移模态的新方法,使得位移模态识别的精度接近频率识别的精度,推导了频率与位移模态关系的理论公式,并给出利用以曲率形式表示的单元模态应变能对结构进行损伤标定的基本方法。最后,通过数值模拟对该方法的有效性进行说明。