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21.
W. Fauriat C. Mattrand N. Gayton A. Beakou T. Cembrzynski 《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2016,54(5):585-605
When assessing the statistical variability of fatigue loads acting throughout the life of a vehicle, the question of the variability of road roughness naturally arises, as both quantities are strongly related. For car manufacturers, gathering information on the environment in which vehicles evolve is a long and costly but necessary process to adapt their products to durability requirements. In the present paper, a data processing algorithm is proposed in order to estimate the road profiles covered by a given vehicle, from the dynamic responses measured on this vehicle. The algorithm based on Kalman filtering theory aims at solving a so-called inverse problem, in a stochastic framework. It is validated using experimental data obtained from simulations and real measurements. The proposed method is subsequently applied to extract valuable statistical information on road roughness from an existing load characterisation campaign carried out by Renault within one of its markets. 相似文献
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《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(12):1797-1816
The railway industry in the UK is currently expanding the use of condition monitoring of railway vehicles. These systems can be used to improve maintenance procedures or could potentially be used to monitor current vehicle running conditions without the use of cost prohibitive sensors. This paper looks at a novel method for the online detection of areas of low adhesion in the wheel/rail contact that cause significant disruption to the running of a network, particularly in the autumn season. The proposed method uses a Kalman–Bucy filter to estimate the creep forces in the wheel–rail contact area; post-processing is then applied to provide information indicative of the actual adhesion level. The algorithm uses data that, in practice, would be available from a set of modest cost inertial sensors mounted on the vehicle bogie and wheel-sets. The efficacy of the approach is demonstrated using simulation data from a nonlinear dynamic model of the vehicle and its track interface. 相似文献
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Poor driving habits such as not using turn signals when changing lanes present a major challenge to advanced driver assistance systems that rely on turn signals. To address this problem, we propose a novel algorithm combining the hidden Markov model (HMM) and Bayesian filtering (BF) techniques to recognize a driver’s lane changing intention. In the HMM component, the grammar definition is inspired by speech recognition models, and the output is a preliminary behavior classification. As for the BF component, the final behavior classification is produced based on the current and preceding outputs of the HMMs. A naturalistic data set is used to train and validate the proposed algorithm. The results reveal that the proposed HMM–BF framework can achieve a recognition accuracy of 93.5% and 90.3% for right and left lane changing, respectively, which is a significant improvement compared with the HMM-only algorithm. The recognition time results show that the proposed algorithm can recognize a behavior correctly at an early stage. 相似文献
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离子迁移谱信号数字滤波和谱峰检测技术 总被引:1,自引:0,他引:1
离子迁移谱信号处理软件主要完成离子迁移谱谱信号的数字滤波和谱峰检测。本文在分析了波形谱图的去噪、滤波和谱峰检测技术的基础上,提出了防脉冲干扰移动平均值法和最小二乘法相结合的数字滤波方法,并采用增加斜率法谱峰检测技术,通过matlab仿真软件验证了数字滤波效果和谱峰检测准确度。仿真试验的结果在离子迁移谱分析仪的应用中取得了较好的效果。 相似文献
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为研究城市快速路合流区车辆运行规律,基于车辆自然轨迹数据,提出考虑驾驶行为异质性的合流区元胞自动机仿真模型。模型将合流区分为上游区域、合流区域及下游区域,3个区域由11条路段组成。首先,利用Kalman滤波算法对自然轨迹数据进行降噪处理;然后,计算每辆车驾驶行为特征参数并进行K-means聚类分析,结合聚类效果评价指标Silhouette系数将驾驶行为分为:保守-谨慎型、激进-谨慎型、保守-轻率型及激进-轻率型这4种类型;最后,依据分类结果,
建立考虑加速度、随机慢化概率异质性的跟驰模型和考虑换道安全间距、换道决策的多级异质性换道模型。在各空间占有率的情境下,基于Matlab进行数值仿真,统计同质驾驶行为和异质驾驶
行为条件下,合流区域车道的流量、密度、速度、时空位置及换道频率等参数。仿真结果表明:在空间占有率为10%~20%时,同质交通流相比异质交通流更容易产生局部交通拥堵和交通流失效情境,并且同质交通流量峰值比异质交通量小27.1%;随着空间占有率的增加,同质车辆和异质车辆驾驶频率均呈现增加-稳定-下降的趋势,而异质驾驶行为换道频率的极大值比同质交通流高
20.74%。 相似文献
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[目的]针对船舶柴油机增压器难以收集到全生命周期性能退化数据的问题,提出一种基于维纳过程的寿命预测模型。[方法]首先,采用K-Means模型对增压器实际运行工况进行聚类,提取出典型工况数据;然后,使用贝叶斯突变点检测模型识别增压器的缺陷点;最后,建立基于维纳过程的退化模型,并以某型船用柴油机增压器为应用对象,预测增压器的剩余使用寿命。[结果]结果显示,基于维纳过程的寿命预测方法能够在不需要同类设备历史退化数据的情况下对增压器的剩余寿命进行预测。[结论]所提方法对缺少故障样本的船舶柴油机增压器寿命预测具有一定的参考价值。 相似文献