Enhancing grey prediction fuzzy controller for active suspension systems

A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results.     

Experimental and numerical investigation on the derailment of a railway wheelset with solid axle

This paper presents the results of an experimental and numerical investigation on the derailment of a railway wheelset with solid axle. Tests were carried out under quasi-steady-state conditions, on a full-scale roller rig, and allowed to point out the effect of different parameters like the wheelset's angle of attack and the ratio between the vertical loads acting on the flanging and non-flanging wheels. On the basis of the test results, some existing derailment criteria are analysed in this paper and two new criteria are proposed. A model of wheel–rail contact is proposed for the mathematical modelling of the flange climb process, and numerical vs. experimental comparisons are used to obtain model validation.     

隧道工程建设地质预报及信息化技术的主要进展及发展方向

复杂的不良地质条件是制约隧道安全高效建设的主要因素,要实现隧道工程的安全高效建设,首先要提高地质预测预报技术水平及其信息化程度。1)介绍我国复杂不良地质隧道超前预报的方法进展及其应用,包括突水突泥灾害源超前探测方法与设备、断层破碎带超前预报、城市地铁溶洞和孤石等探测的进展及应用等;2)介绍我国隧道岩爆监测预警方法及其应用,预报清楚之后就要加强安全风险过程监控;3)介绍基于BIM技术的建筑物(隧道工程)安全风险监控最新进展,包括安全风险实时感知系统和实时预警系统;4)指出隧道工程建设信息化技术的发展方向,包括开展基于大数据技术的TBM/盾构施工的分析与控制研究以及数字隧道向智慧隧道(建设和运营维护)的发展。     

多元评价体系组合模型在铁路隧道变形预测中的应用

为克服传统预测模型结构单一、预测精度及稳定性不足等缺陷,提出多元体系组合预测模型的建模思路。首先,基于支持向量机、BP神经网络及ARMA模型3种单一预测模型,构建铁路隧道变形预测体系;再以均方根误差、误差平方和及平均绝对误差等为评价准则或指标,构建各预测结果的误差评价体系,求解各单项预测模型的权值贡献指数,得到最优组合权值;然后利用后验差检验、残差检验和关联度检验构建预测精度校验体系,对组合预测结果进行检验,评价预测模型的有效性;最后,结合工程实例,对多元体系组合预测模型在特大断面隧道中的变形预测效果进行检验。结果表明:多元评价体系组合模型预测相对误差值均小于2%,具有较高的预测精度,且较单一预测模型具有更高的预测精度,也一致通过相关检验,验证了多元体系组合预测模型的有效性。     

基于路网容量的商圈停车需求预测研究

分析商圈停车、交通拥堵与商圈持续繁荣的关系,商圈停车需求预测对商圈的可持续发展起着重要作用。为合理预见与科学估算商圈停车需求,结合路网容量、区位关系提出基于路网容量的停车需求预测模型。该模型一方面能平衡区域停车供需,缓解静态设施供需矛盾;另一方面能保证停车需求与路网容量相匹配,对动态交通起到必要的控制作用,缓解商圈周边路网的交通拥堵。最后,通过实例分析证明该模型的可行性。     

备件消耗预测方法研究现状及发展

备件消耗预测是制定备件消耗标准的基础工作之一,通过对国内外有关备件消耗预测的文献进行研究,在分析当前备件分类的基础上,总结消耗连续型备件和消耗间断型备件的消耗预测方法研究现状,指出不同类型消耗预测模型的优点及存在的不足,揭示了备件消耗预测的研究重点及发展趋势。     

城市轨道交通列车噪声预测模型研究

以已建立的城市轨道交通噪声预测模型为基础,提出改进的噪声预测模型。明确了各预测参数,采用对数回归关系确定了各影响因子与等效声级的关系。运用预测模型对长春轻轨噪声进行了预测。通过与实测结果进行比较,预测值与实际结果的误差<1dB(A),表明所提出的预测模型可精确反映长春轻轨的噪声级。     

Study of automatic designing of line heating technique parameters

1Introduction Lineheatingisashellplateheatprocessingmethod usedinshipbuildingproduction.Itisacomplexand difficulttechnique,mainlyusedindoublebending shellplateforming.Becausetherearemanyinfluence factorsinplateforming,theinfluencedisciplineis hardtopredic…     

半潜式起重船波浪载荷预报

采用数值分析软件Sesam/HydroD对某半潜式起重船在航行状态和起重作业状态下的波浪载荷进行长期预报和短期预报.在航行状态下,预报得到的最大波浪弯矩和剪力分别为规范值的1.4倍和2.0倍,用于进行结构疲劳评估(超越概率为10-2)的波浪弯矩最大预报值约为用于进行结构强度评估(超越概率为10-8)的波浪弯矩最大预报值...     

Assessment of factors associated with travel time reliability and prediction: an empirical analysis using probabilistic reasoning approach

Significant efforts have been made in modeling a travel time distribution and establishing measures of travel time reliability (TTR). However, the literature on evaluating the factors affecting TTR is not well established. Accordingly, this paper presents an empirical analysis to determine potential factors that are associated with TTR. This study mainly applies the Bayesian Networks model to assess the probabilistic association between road geometry, traffic data, and TTR. The results from this model reveal that land use characteristics, intersection factors, and posted speed limits are directly associated with TTR. Evaluating the strength of the association between TTR and the directly related variables, the log odds ratio analysis indicates that the land use factor has the highest impact (0.83) followed by the intersection factor (0.57). The findings from this study can provide valuable resources to planners and traffic operators in their decision-making to improve TTR with quantitative evidence.