振动
均方根
航程(航空)
卡车
有效载荷(计算)
路面
统计分析
计算机科学
统计
环境科学
汽车工程
工程类
数学
声学
计算机网络
物理
土木工程
航空航天工程
网络数据包
电气工程
作者
Matthew Lamb,Vincent Rouillard
摘要
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.
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