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On the parameters that influence road vehicles vibration levels
Packaging Technology and Science ( IF 2.6 ) Pub Date : 2021-05-30 , DOI: 10.1002/pts.2592
Matthew James Lamb 1 , Vincent Rouillard 1
Affiliation  

It has long been recognised that the level of road vehicle vibrations are mainly a function of vehicle characteristics, road roughness and vehicle speed. With the introduction of easy-to-use vibration data recorders, significant amounts of data have been recorded, and numerous studies on the rms levels of truck vibrations have been published. However, the results available to date are typically from specific scenarios and do not provide comprehensive comparisons with similar published work. In addition, most of the publications only report the mean rms level with no indication of how the rms varies throughout the journey nor statistical information on the likelihood of particular rms levels being exceeded. This paper brings together the available information on road transport vehicle vibration levels for analysis. It does so by first collating published mean vibration rms values for a broad range of scenarios and supplements them with additional mean rms values recorded by the authors. The collated results were analysed statistically to reveal the influence of important parameters, namely, suspension type, road type, payload and vehicle type. Results from the statistical analysis are used to quantify the influence of each parameter and to allow for the prediction of expected rms levels based on the transport scenario. This introduces a risk-based approach to laboratory testing which allows the analyst to set the test rms levels based the road transport scenario and the accepted level of risk.

中文翻译:

影响道路车辆振动水平的参数

人们早就认识到道路车辆振动的水平主要是车辆特性、道路粗糙度和车速的函数。随着易于使用的振动数据记录器的推出,大量数据已经被记录下来,并且已经发表了大量关于卡车振动均方根水平的研究。然而,迄今为止可用的结果通常来自特定场景,并没有提供与类似已发表工作的全面比较。此外,大多数出版物仅报告平均 rms 水平,没有说明 rms 在整个旅程中如何变化,也没有关于超出特定 rms 水平的可能性的统计信息。本文汇集了有关道路运输车辆振动水平的可用信息进行分析。为此,它首先整理已发布的各种场景的平均振动 rms 值,并用作者记录的其他平均 rms 值对其进行补充。对整理的结果进行统计分析,揭示重要参数的影响,即悬架类型、道路类型、有效载荷和车辆类型。统计分析的结果用于量化每个参数的影响,并允许根据运输场景预测预期的均方根水平。这引入了一种基于风险的实验室测试方法,允许分析人员根据道路运输场景和可接受的风险级别设置测试有效值级别。对整理的结果进行统计分析,揭示重要参数的影响,即悬架类型、道路类型、有效载荷和车辆类型。统计分析的结果用于量化每个参数的影响,并允许根据运输场景预测预期的均方根水平。这引入了一种基于风险的实验室测试方法,允许分析人员根据道路运输场景和可接受的风险级别设置测试有效值级别。对整理的结果进行统计分析,揭示重要参数的影响,即悬架类型、道路类型、有效载荷和车辆类型。统计分析的结果用于量化每个参数的影响,并允许根据运输场景预测预期的均方根水平。这引入了一种基于风险的实验室测试方法,允许分析人员根据道路运输场景和可接受的风险级别设置测试有效值级别。
更新日期:2021-08-05
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