基于大数据挖掘的汽车振动阈值研究

Puchao Li, Dongyu Li, Mian Wang
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引用次数: 0

摘要

为了排除振动的知觉差异不同的测试人员和帮助有关当局计划维护和确定的时间线维修,车辆抖动阈值进行了分析,使它的一个预测因素持续车辆抖动和在一定程度上排除干扰的测试人员的生理感觉。根据收集的加速度信号测试、频谱分析和骑和舒适指数计算。当接近阈值且趋势持续增加时,即平顺性指数大于1.6-1.8,舒适性指数大于0.7-0.9,横向主频6-9Hz,纵向主频6-9Hz和12-15Hz,应提前检查车辆和线路并进行针对性管理,如果接近阈值但变化趋势平缓,可以暂时不采取治理手段,但需要加强监测;各类监测指标的采集超过阈值并有持续增加的趋势,建议对车辆和线路进行检查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on vehicle vibration threshold based on big data mining
In order to exclude differences in the perception of vibration by different testers and to help the relevant authorities to plan maintenance and determine the timing of line repairs, the vehicle jitter threshold was analysed to make it one of the predictors of sustained vehicle jitter and to exclude to a certain extent the interference of the testers' physical sensations. According to the acceleration signal collected by the test, spectrum analysis and ride and comfort index calculation. When it is close to the threshold and the trend continues to increase, i.e. ride index is greater than 1.6-1.8, comfort index is greater than 0.7-0.9, lateral main frequency 6-9Hz, vertical main frequency 6-9Hz and 12-15Hz, the vehicle and line should be checked in advance and targeted management, if close to the threshold but the trend of change is gentle, the means of governance can be temporarily not taken, but need to strengthen the monitoring, collection of various types of monitoring indicators exceed the threshold and there is a continuous trend of increase, it is recommended that the vehicles and lines are inspected.
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