共查询到20条相似文献，搜索用时 203 毫秒
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对城市轨道交通车辆的车下制动设备模块化设计进行了探讨,详细介绍了制动设备的模块化设计方法,并且总结了制动设备模块化设计优点。 相似文献
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车流量的不断增大,城市变得愈加拥挤,需要进行车辆密度估计,进而构建有效的车辆防碰撞系统。提出一种基于随机寻址RFID阵元分布的车辆密度参量估计算法,进行ZigBee和参量估计的车辆防碰撞预警系统设计。首先实现了基于ZigBee的车辆间的通信组网系统模型构建,得到了ZigBee组网与车辆碰撞预警方法,利用随机寻址RFID方法进行ZigBee的车辆间的通信组网系统模型构建,采用贝叶斯近似方法建立均匀矩形阵列,车辆作为阵元分布在均匀矩形网格中,以此描述车流动态变化过程,根据角度变化得到车流的方位和速度信息,实现车辆密度参量估计和防碰撞预警系统设计。系统实验结果表明,该算法和系统进行车辆密度参量估计,估计精度较高,信息全面准确。通过准确的车辆密度参量估计,提高了车辆防碰撞预警系统的性能。 相似文献
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西安地铁车辆合成闸瓦技术方案初探 总被引：1，自引：0，他引：1
本文分析了国内外地铁车辆应用的合成闸瓦技术,并对所使用的合成闸瓦特点进行探讨。提出研究聚合物基复合摩阻材料的地铁车辆合成闸瓦初步技术方案,着重解决适用于西安地铁车辆制动工况的关键技术,包括耐热高聚物的改性和应用研究、增强材料的应用研究和设计材料结构与性能,并对合成闸瓦的国产化进行初步探讨。 相似文献
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高温季节车辆具有充气系数下降、润滑油容易变质、机器零件易烧损、制动性能变差等特点,对车辆进行维护保养的重点在于防轮胎爆炸、防润滑油变质、防刹车失灵等. 相似文献
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交流机车的接地和搭接设计是车辆系统中的重要部分。如果该部分设计不完善会影响车辆的电磁兼容（EMC）性能,从而造成车辆电气总体性能的下降。为规范该部分设计,本文从五个方面进行了分析、总结,从而达到提高车辆接地和搭接性能的目的。 相似文献
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智能车辆是智能交通系统研究的热点领域,开展智能车辆的障碍物检测技术研究,是车辆辅助驾驶及无人驾驶的关键技术之一。随着计算机硬件的快速发展,计算性能不断提高,一些新的算法或方法也不断被提出,而障碍物检测技术仍然是智能车辆研究的重点和难点。文章介绍了双目立体视觉相关的一些理论,对近年来的一些基于双目立体视觉的障碍物检测方法分析并进行综述。 相似文献
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由于车辆原因造成的交通事故中,有80%是因车辆性能引起的,车辆性能是否良好,直接关系到汽车的行驶安全。根据事故现场的车轮制动印迹可判断轮胎规格、行驶路线、方向、车速等,从而判断驾驶员行为,对于制定交通事故预防方案、处理交通事故具有十分重要的意义。 相似文献
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机动车的制动性能是使车辆安全行驶的重要屏障,所以对机动车的制动性能检测成为车辆安全检测的一个重要环节.根据调查发现,在发生机动车事故中最为严重的因素就是机动车的制动性能差,只有保证机动车拥有良好的制动性能,才能确保机动车安全的行驶.所以,我们要重视机动车的制动性能,经常的对制动系统进行安全检测.但在实际检测中,影响机动车安全制动性能检测结果的因素有很多.
一、检测结果会受到检测设备的影响
1.1制动检验台的结构对检测结果的影响
根据GB72578-2012《机动车运行安全技术条件》的规定,机动车的制动性能安全检测分为测按照检测动态路试方法和静态台式方法两种.其中,台式制动性能检台功能原理分为滚筒反力式制动检验台和平板式制动检验台,这两种制动检验台可以准确的检测评价机动车的安全制动性能,检测结果更加科学和准确的. 相似文献
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本文从摩托车制动性能评价指标和人机工程学原理出发，导出了液压盘式制动器的设计计算方法和步骤。并时制动系统的参数进行了分析计算，对各个部件的控制要素进行了评价。 相似文献
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《Journal of The Franklin Institute》2022,359(17):10120-10144
In this paper, a Fault Detection and Isolation (FDI) system based on an ensemble-based hierarchical classifier is devised to detect and isolate twelve typical turbine faulty scenarios and a healthy scenario. The hierarchical classifier is designed based on eight studied classifiers' best-practice confusion patterns, ranging from classical to state-of-the-art methods. The proposed hierarchical classifier discriminates five faulty classes with almost perfect accuracy while increasing the accuracy of healthy scenario discrimination by 10%, which is particularly important since it significantly reduces the false alarm rate for any form of fault. The overall accuracy of classification is improved by 2%, as well. Along with the classifier, an appropriate notion of confidence rate helps evaluate the classifier's decisions, especially when unlabeled data are involved. This motivation leads to devising a confidence rate concept that suits the devised classifier well. The obtained results show that the introduced confidence rate changes monotonically with classification accuracy. In the case of the high confidence rate of unlabeled data, this property is utilized to label the data with high accuracy. The proposed confidence rate is particularly effective in decision-making in the labeling of challenging mixed-up scenarios. Obtained results show that the classifier's decisions are reliable, with a confidence rate greater than 0.7. The developed FDI system is examined with simulated and real data, where obtained results verify the satisfactory performance of the system. 相似文献
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光学模式识别是模式识别的一个重要分支,它以光学相关与数字处理相结合的方式实现对图像信号的处理与识别,具有光速运算、高速并行处理、高分辨率的突出优点。本文根据光学匹配滤波的理论,用Matlab软件模拟了光学模式识别,得到了与理论一致的结果。 相似文献
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为了研究车辆在桥面上行驰过程中突然刹车对桥梁产生的冲击振动的影响,考虑了车轮处的摩擦力与刹车制动力共同作用时移动质量模型对车桥的耦合振动现象进行数值模拟。对于工程中常用的变截面箱梁,推导了平面内呈线性和抛物线形变化时的质量阵,采用Romberg数值积分方法得到刚度矩阵中的系数项。对于变速行驰在桥面上的车辆出现紧急刹车的现象,考虑了车轮与桥面间的摩擦并引入冲击系数模拟刹车力对桥面的作用,探讨了摩擦系数与冲击系数对车桥耦合振动的影响。 相似文献
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《Journal of The Franklin Institute》2022,359(16):8497-8521
In order to improve the response speed and control precision of the braking system with parameters uncertainty and nonlinear friction, a braking-by-wire system based on the electromagnetic direct-drive valve and a novel cascade control algorithm was proposed in this paper. An electromagnetic linear actuator directly drives the valve spool and rapidly adjusts the pressure of braking wheel cylinders. A dynamic model of electromagnetic direct-drive valve considering improved LuGre dynamic friction is established. A novel cascade control algorithm with an outside loop pressure fuzzy controller and an inside loop electromagnetic direct-drive valve position controller was proposed. An adaptive integral robust inside loop controller is designed by combining friction compensation adaptive control law, linear feedback, and integral robust control. The uncertainty parameters and the friction state are estimated online. The stability of the cascade controller is proved by the Lyapunov method. Then a multi-objective opitimizemization design method of control parameters is proposed, which combines a multi-objective game theory and a technique for order preference by similarity to ideal solution (TOPSIS) based on entropy weight. The results show that the pressurization time of cascade control is less than 0.09 s under the 15 MPa step target signal. The control precision is improved effectively by the cascade controller under the ARTEMIS condition. 相似文献
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《Information processing & management》2016,52(5):885-910
One of the important problems in text classification is the high dimensionality of the feature space. Feature selection methods are used to reduce the dimensionality of the feature space by selecting the most valuable features for classification. Apart from reducing the dimensionality, feature selection methods have potential to improve text classifiers’ performance both in terms of accuracy and time. Furthermore, it helps to build simpler and as a result more comprehensible models. In this study we propose new methods for feature selection from textual data, called Meaning Based Feature Selection (MBFS) which is based on the Helmholtz principle from the Gestalt theory of human perception which is used in image processing. The proposed approaches are extensively evaluated by their effect on the classification performance of two well-known classifiers on several datasets and compared with several feature selection algorithms commonly used in text mining. Our results demonstrate the value of the MBFS methods in terms of classification accuracy and execution time. 相似文献
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传统的神经网络对于简单、具有明确分类界限的数据,可以有较好的计算结果,但是在输入属性集合较大、分类界限不明确的情况下,会出现收敛效率和分类准确率较低,甚至会出现不收敛状态。本文利用Rough集的理论,对输入数据不停地进行样本检测,对输入特征不停地进行筛检,以此达到删减输入特征数的目的,从而提高对输入数据的拟合。通过对采集到的脑电信号进行验证,达到删减特征数和提高分类准确度的目的。 相似文献