和谐系列内燃机车用大功率柴油机试验研究

根据和谐系列大功率内燃机车型式试验的试验数据,着重分析了能够对内燃机车运用性能产生重大影响的一些柴油机关键性指标:柴油机功率、冷却系统性能、排放性能、经济性,并探讨了今后国内机车柴油机研究的工作重点.     

我国内燃牵引动力国产化工作重点及再创新发展方向

基于铁路内燃牵引动力技术平台的发展,论述了我国机车柴油机在关键部件国产化及试验方面的重点工作,并从机车柴油机核心部件研发、加强信息化管理等方面阐述了今后应注重和推进的再创新发展方向。     

过载条件下固体发动机药柱结构完整性分析

基于三维线性粘弹性积分本构关系，采用有限元法，对固体火箭发动机的药柱结构在复杂载荷作用下的瞬态响应进行了数值模拟。药柱结构计算分析模型由发动机主要零部件壳体、隔热层和药柱构成，药柱和隔热层采用粘弹性本构模型。分别计算分析了轴向和轴向与横向同时过载条件下药柱结构的应力应变响应，讨论了复杂载荷作用下药柱结构的应力分布、变形特征和局部危险部位。研究工作为药柱结构中各类损伤规律的深入讨论，为固体火箭发动机的设计和结构完整性分析提供一定的参考。     

内燃机活塞温度场的轴对称组合边界元分析

采用常数-线性组合边界元计算轴对称热传导问题,既可减小奇异点计算的困难性,又提高了计算精度。本文运用FORTRAN77算法语言编制了包含有三种类型边界条件在内的轴对称组合边界元分析程序,具体分析了6135ZG柴油机活塞的温度分布。结果表明,应用边界元法分析轴对称活塞温度场,计算工作量比有限元的计算量显著减少,而计算结果同有限元结果吻合得较好,与实际测量结果相比,最大相对误差仅为1％。     

柴油机冷却系统的维护与保养

为了避免船舶柴油机由于冷却系统工作不良而导致损坏 ,提出了气缸冷却水设计要求及冷却水质量控制要求     

甲醇—异辛烷混合燃料滞燃期研究

对Curran的异辛烷详细化学动力学机理和Li的甲醇化学动力学机理进行了甲醇着火滞燃期特性对比研究,发现Curran异辛烷机理基本能反映甲醇的自燃着火过程。基于此,利用Curran异辛烷机理对甲醇—异辛烷混合燃料在初始温度为600 K~1 600 K、压力为1.0 MPa~4.0 MPa、当量比为0.3~1.5范围内的着火滞燃期特性进行了计算研究,分析燃料特性和初始条件对混合燃料滞燃期的影响。结果表明,初始温度对甲醇—异辛烷混合燃料的滞燃期影响较大,当初始温度增加时,滞燃期大幅缩短;部分掺醇混合燃料(掺醇率低于25%)中甲醇含量对燃料滞燃期的影响因温度范围的不同而不同,在850 K以下甲醇比率增加使混合燃料滞燃期延长,在850 K以上甲醇比率增加使其滞燃期缩短。     

点火正时对电控稀燃天然气发动机性能的影响

试验研究了点火正时对电控稀燃多点喷射天然气发动机燃烧及排放性能的影响规律。对该发动机转速为1 450 r/min,1 750 r/min,2 050 r/min,负荷为25%,50%,75%,100%的12个工况点进行了试验研究。研究结果表明,在其他燃烧边界条件不变的情况下,点火正时对该发动机输出扭矩及CH4排放影响不大,但是在2 050 r/min,100%负荷工况下,随着点火正时的进一步后移,出现扭矩下降及CH4排放增加的现象。点火正时对NOx排放有显著的影响,同一工况下,随着点火正时的推移,NOx排放明显降低。     

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.     

An inference engine for smartphones to preprocess data and detect stationary and transportation modes

A smartphone can be utilized as a cost-effective device for the purposes of intelligent transportation system. To detect the movement and the stationary statuses in the motorized and non-motorized modes, this study develops a new inference engine, including two sets of rules. The first sets of rules are defined by the related thresholds on the features of smartphone sensors while the second sets are extracted from the human knowledge to improve the results of the first rules. The experimental results reveal that by utilizing Inertial Measurement Unit (IMU) sensors in the proposed inference engine, it is possible to save 40% energy in comparison with the previous research. Moreover, this engine increases the accuracy of the motorized mode detection to 95.2% and determines the stationary states in motorized mode with 97.1% accuracy.