沫水船闸短廊道输水系统布置及试验研究

以沫水船闸工程为依托,建立几何比尺为1∶20的物理模型试验,对短廊道输水系统的水力特性进行研究。针对上闸首出流不均匀的现象提出了新型高效的T型消力梁方案,对下闸首进口存在串通漏斗旋涡的问题提出了扩大泄水廊道进口尺寸的措施。试验表明:优化消能工后,最大横向系缆力减小幅度可达50%,各项水力指标满足规范要求。该研究为沫水船闸设计提供了科学依据,并可为其他短廊道输水系统船闸设计提供参考。     

A Generalized Rough Set Approach to Attribute Generalization in Data Mining

This paper presents a generalized method for updating approximations of a concept incrementally, which can be used as an effective tool to deal with dynamic attribute generalization. By combining this method and the LERS inductive learning algorithm, it also introduces a generalized quasi-incremental algorithm for learning classification rules from data bases.     

一种步进电机控制的气体压力闭环控制系统的设计与实现

介绍了一种步进电机控制的气体压力闭环控制系统。该系统的主控计算机根据气体实际注入情况和预期的注入设定值进行准确计算后,控制步进电机驱动卡驱动相应的步进电机,调节精密减压器的开度,从而确保工作气体的长时间、高精度恒压注入。本系统具有控制精度高、控制速度快、通用性好、价格低等特点。     

变频调速系统共模电流耦合干扰研究

现代变频调速系统多为电压源逆变器驱动感应电机的拓扑形式。逆变器由快速开通和关断的IGBT产生高频和快速上升和下降的脉宽调制电压,在系统中产生严重的共模电流干扰。长的电机驱动电缆中的干扰电流会通过感性或容性耦合的形式将干扰引入到周围的其它电路中去。本文主要研究了典型交流电机驱动系统与敏感电子设备共用接地平面时的感性耦合干扰,给出了分析耦合干扰的模型和实验结果。     

地铁车辆客室车门监控功能的优化设计

阐述了深圳地铁一期工程列车客室车门监控的实现原理,并结合车门系统在实际应用中所出现的问题,分析了该车门系统故障诊断存在的设计缺陷,并提出相应的完善技术方案。     

高速铁路牵引变电所负荷试验方法探讨

介绍了高速铁路牵引变电所负荷试验的几种方法,阐述了移动电容器法和牵引变环流法及其试验设备的选择、步骤和关键的计算。     

汽车交流发电机纹波电流及其抑制

内部装置有整流器和电压调节器的汽车交流发电机，其输出的直流电势会有较大的纹波分量。和名牌发动机配套的发电机，在一定转速下的纹波电流也是一项主要性能参数。本文简介过大的纹波电流造成的影响，分析纹波电流的形成，重点论述设计和制造中如何测量和抑制纹波电流，以满足产品达到出口配套的技术要求。     

集成化仿真系统在气制动TCS控制器开发中的应用

利用Simulink/xPC实时仿真软硬件环境,设计了集成化TCS仿真软硬件系统。建立了包括整车、动力传动系、制动器、轮胎、路面的动力学模型,应用离线仿真、快速原型仿真和ECU在环仿真等方法开发了气制动TCS控制器控制逻辑。经实车试验表明,系统能有效控制驱动轮的打滑趋势,提高汽车加速性能,改善发动机的工作条件。     

半实物仿真环境下大功率逆变器建模的补偿算法

在交流传动半实物仿真系统中．由于控制器和仿真器的不同步以及仿真器硬件计算能力对仿真模型采样周期的限制．异步电机的电流波形在低速段严重畸变．磁链和转矩在整个调速区间都存在明显的失真。针对这些问题．在逆变器建模过程中,提出了一种等磁链电压补偿算法：试验结果表明该算法有效地克服了上述失真现象,取得了较理想的仿真效果。     

Soft Radial Basis Cellular Neural Network (SRB-CNN) based robust low-cost truck detection using a single presence detection sensor

This paper does present a comprehensive concept for a robust and reliable truck detection involving solely one single presence sensor (e.g. an inductive loop, but also any other presence sensor) at a signalized traffic junction. Hereby, two operations modes are distinguished: (a) during green traffic light phases, and (b) a much challenging case, during red traffic light phases. First, it is shown how difficult the underlying classification task is, this mainly due to strongly overlapped classes, which cannot be easily separated by simple hyper-planes. Then, a novel soft radial basis cellular neural/nonlinear network (SRB-CNN) based concept is developed, validated and extensively benchmarked with a selection of the best representatives of the current related state-of-the-art classification concepts (namely the following: support vector machines with radial basis function, artificial neural network, naive Bayes, and decision trees). For benchmarking purposes, all selected competing classifiers do use the same features and the superiority of the novel CNN based classifier is thereby underscored, as it strongly outperforms the other ones. This novel SRB-CNN based concept does satisfactorily fulfill the hard industrial requirements regarding robustness, low-cost, high processing speed, low memory consumption, and the capability to be deployed in low cost embedded systems.