装配式梁桥横向协同工作性能度量指标的研究

为了表征运营期间装配式梁桥的横向协同工作性能,提出了一种间接度量指标——相邻预制梁间的应变相关系数;同时建立了装配式梁桥的简化力学模型,通过推导建立了该指标的解析表达式。理论分析和数值仿真研究表明,在保证足够的样本长度条件下,交通流荷载趋向统计稳定,此时结构特性成为该度量指标的唯一影响因素,证明了该指标具备表征装配式梁桥横向协同工作性能的条件。     

基于相关性精简关联规则生成算法

针对传统基于支持度-置信度桩架关联规则挖掘算法生成规则只考虑支持度和置信度的因素、没有考虑规则两者本身内在的关系并因此产生大量无效的规则的情况,提出了一种采用相关性精简关联规则产生的算法,此算法增加了一个度量——相关性来精简关联规则的产生。实验表明该算法在继承传统算法的优点的同时在一定的程度上提高了规则的有效性,降低规则冗余。     

声相关计程仪的工作原理与适用性

声相关计程仪是一种利用波形不变性原理制成的自主式测速导航设备。即便在GPS导航高速发展、INS系统已提高到很高精度的今天,声相关计程仪仍然有其不可替代的导航作用,尤其在军事领域更是如此。通过介绍船用声相关计程仪的基本原理及其应用范围,阐明声相计程仪的组成各部分作用特点及其适用性。     

极线约束下的多分辨率相关匹配算法

针对计算机视觉在几何测量应用中图像匹配特点,提出了将多分辨率和极线约束与相关法相结合的图像匹配方法。该方法采用金字塔分层和极线约束来弥补相关匹配带来运算量大的不足,克服了图像匹配中精度低的缺点。通过计算机视觉在几何测量检测系统中图像匹配的实际应用,验证了该算法具有较高的测量精度、速度及其实用性。     

Links between subjective and objective evaluations regarding the steering character of automobiles

This work presents an experiment on the relationships between subjective and objective evaluations of vehicle handling. Ten cars were examined objectively in several open-loop driving dynamics manoeuvres and subjectively by test persons in typical traffic situations. Results are extracted from a stationary test (the Slowly Increasing Steer Test), and a dynamical test (the Frequency Response Test). The subjective measurements are obtained from drivers on a rural road course via a questionnaire, which was developed to separately investigate the quantity level perception, the so-called “Niveau”, and the more qualitative “Liking”. These subjective “measurements” are embedded into a two-channel definition of “Steering Comfort” as a genus for “Steering Discomfort” and “Character”. The article concentrates on developing a statistical method for the consideration of correlations amongst the subjective/objective data. In doing so, the variance in example subjective Niveau ratings can be significantly explained by several objective quantities. Indicators for co-domains of validated discomfort characteristics and hints for endeavouring character Liking ranges are detected.     

Bolster spring fault detection strategy for heavy haul wagons

An on-board health monitoring system is proposed for heavy haul wagons in this paper including a signal-based fault detection and isolation (FDI) method and an on-line fault diagnose strategy. Such a system, to be feasible on freight wagons, must be sufficiently cheap and robust, hence the design assumes the constraint of using only two accelerometers mounted on the front left and right rear part of each carbody in a heavy haul train. This paper focuses on the detection of bolster spring fault conditions. The problem is made more complex by the modes of failure which might be expected in bolster spring nests. Types of spring failure are firstly identified and discussed covering situations of broken (shortening springs) and softening (individual spring loss from a nest or cross-section loss through corrosion). The effects of these faults and their detectability were investigated using simulations on straight and curved track and using a fully detailed model of a typical 40?t axle-load heavy haul wagon. The simulation results were then examined and compared using cross-correlation analysis and an FDI system was proposed. The FDI system introduced five possible fault indicators. Initial results indicated that it was possible to detect changes in bolster stiffness of ±25%. An on-line fault diagnoses strategy is proposed for bolster spring faults which only requires data from wagon monitoring during travel around sharp curves to detect and the occurrence of confirm faults. The functionality envisaged needs only a ‘once per trip’ monitoring site, such as a sharper curve, and is aimed at condition monitoring rather than the provision of alarms or comprehensive monitoring of all events.     

基于遗传算法和极限学习机的智能算法在基坑变形预测中的应用

为解决传统智能算法网络结构参数复杂、运算速度慢等问题,基于遗传算法和极限学习机构建基坑变形的新型优化智能预测模型。先利用皮尔逊相关系数评价不同影响因素与基坑沉降变形之间的相关性,以确定极限学习机的输入层; 再采用试算法确定最优激励函数和隐层节点数,并将遗传算法和极限学习机耦合,利用遗传算法优化极限学习机的初始权值和阈值,以提高预测精度。经实例检验表明： 1)开挖时间、开挖深度、土体抗剪参数及重度均与基坑沉降变形显著相关,为构建极限学习机输入层提供了依据; 2)在预测过程中,激励函数和隐层节点数对极限学习机的预测效果具有一定的影响,以Sigmiod型激励函数和13个隐层节点数的预测效果为最优; 3)通过遗传算法的优化,能进一步提高预测精度,验证了遗传算法的优化能力和有效性。预测模型在不同工况下的预测结果均较优,说明该模型具有较高的稳定性和可靠性。     

改性沥青中SBS含量的灰色关联度分析

为分析性能指标随SBS含量的变化趋势及敏感性,避免由单个指标确定SBS含量所带来的偏差较大的问题,采用灰色关联度分析沥青针入度、软化点、5℃延度、弹性恢复、135℃运动黏度等性能指标与SBS含量的关联性,从而确定改性沥青的SBS含量控制关键指标,并综合关联度高的指标来确定SBS的含量。结果表明改性沥青性能与SBS含量有着相关性,SBS含量对沥青的135℃运动黏度、弹性恢复、软化点、延度、针入度均有影响,其中对135℃运动黏度影响最为显著,沥青的软化点、弹性恢复、135℃运动黏度等指标与SBS含量有着较高的关联度。建立了基于软化点、弹性恢复、135℃运动黏度等性能指标的改性沥青中SBS含量的确定方法,其误差小于4%。     

EEMD和SVM在发动机故障诊断中的应用

针对发动机缸盖振动信号的非线性非平稳特征,提出一种总体平均经验模态分解(EEMD)和支持向量机相结合的信号分析及故障诊断方法,该方法利用EEMD算法以及IMF序列和原始振动信号之间的相关系数,有效放大故障诊断特征向量的差异。对原始振动信号进行EEMD分解,得到各阶特征模态函数(IMF),求各阶IMF分量对应于原始信号的相关系数并组成故障分类特征向量。分别将IMF相关系数法和IMF能量分布法得到的特征向量作为输入,建立BP神经网络和支持向量机,判断发动机工作状态和故障类型。分析表明,对IMF求相关系数的方法简便易行,能有效放大不同工况下特征向量的差异,结合支持向量机能够对既定机型的配气机构和点火系常见故障进行准确识别。     

一种设计潮位推算方法在深水筑港中的应用

深水筑港是港口建设的趋势。文章探讨了确定深水筑港设计潮位的一种方法,阐述了基于潮流数学模型的设计潮位推算方法,用实际资料验证了该方法。结果表明:该方法有较高的计算精度,用于确定深水筑港的设计潮位是合理的、可行的。