大宇王子轿车微机控制点火系统原理与故障诊断

大宇王子轿车微机控制 火系统主要点火线圈，点火器，曲轴位置传感器和电子控制器等组成，介绍了该点火系统工作原理和各主要元器件的功能，并对系统故障的诊断与检修进行了说明。     

定时误差对部分并行干扰消除检测器的影响

重点分析了基于硬判决的部分并行干扰消除(PPIC)检测器的残余多址干扰的结构及统计特性,研究了PPIC在定时跟踪误差情况下的性能,并给出了其在定时误差跟踪下的封闭形式的误码表达式。实验表明:采用部分干扰因子可以抑制PIC系统性能恶化,而基于文献[4]给出的部分干扰因子可进一步改善系统性能。     

北斗授时技术在高速铁路信号系统地面设备时钟同步中的应用

利用北斗授时技术实现高速铁路信号系统时钟自动同步,有利于提高系统信息安全和维护水平,但目前北斗授时技术在铁路信号系统中尚无应用先例。结合高速铁路信号系统地面设备时钟同步应用现状,分析信号地面设备时钟同步需求;通过分析世界上主流卫星导航系统优缺点,结合中国铁路信号系统需求,选择北斗授时技术作为高速铁路信号系统地面设备的时钟同步技术;构建基于北斗授时技术的总体方案和具体应用方案;最后对时钟同步设备功能、系统接口和测试方案进行说明。研究成果已在中国铁路广州铁路局集团有限公司广深线实施,实现了信号系统地面设备的时钟自动同步。     

数字式点火模块自适应控制的研究

采用了在常规汽油机上仅利用分电器输出的点火触发信号进行点火提前和点火能量自适应控制的方法；根据国家有关标准进行了自适应点火控制模块的软硬件设计，经道路和发动机台架试验证明该点火器能在一定程度上提高使用车辆的经济性。     

克莱斯勒轿车无分电器点火系的故障诊断与检修

克莱斯勒汽车公司的君王、纽约客、LHS及前景牌轿车的3．3L、3．5L V6发动机均采用无分电器点火系。该点火系统由点火线圈组件、曲轴位置传感器、动力控制模块(PCM)、继电器等组成。介绍了发动机不能起动的检测与利用故障码诊断技术。另外，介绍了点火线圈的检查，曲轴位置传感器与凸轮轴位置传感器的检查，火花塞的检查方法等。     

An Exploration of the Relationship between Timing and Duration of Maintenance Activities

The timing and duration of an activity episode are two important temporal aspects of activity-travel behavior. Understanding the causal relationship between these two variables would be useful in the development of activity-based travel demand modeling systems. This paper investigates the relationship between these two variables by considering two different causal structures – one structure in which time-of-day choice is determined first and influences duration and a second structure in which activity duration is determined first and affects time-of-day choice. These two structures are estimated within a discrete-continuous simultaneous equations framework employing a full-information maximum likelihood methodology that allows error covariance. The estimation is performed separately for commuter and non-commuter samples drawn from a 1996 household travel survey data set from the Tampa Bay area in Florida. The results of the model estimation effort show that the causal structure in which activity duration precedes or affects activity timing (time of day choice) performs better for the non-commuter sample. For the commuter sample, the findings were less conclusive with both causal structures offering equally good statistical measures of fit. In addition, for the commuter sample, all error correlations were found to be zero. These two findings suggest that time of day choice and activity episode duration are only loosely related for the commuter sample, possibly due to the relatively non-discretionary and inflexible work activity and travel.     

发动机点火波形与故障分析

点火波形是发动机点火系工作时点火线圈初级、次级电流及电压随时间（或曲轴转角）变化的关系在专用示波器上的显示，它实时地反映了点火系的工作状况。因此，点火系的故障也必然反映在点火波形上。分析了点火波形的形成、影响点火波形的因素     

谈6135D型柴油机配气相位的检查与调整

分析了柴油机配气相位正确与否，对内燃机工作的影响和排除配气相位不正时故障的具体操作方法和步骤，以及正时齿轮无记号时的装配要领。     

Methods to reduce dimensionality and identify candidate solutions in multi-objective signal timing problems

Adjusting traffic signal timings is a practical way for agencies to manage urban traffic without the need for significant infrastructure investments. Signal timings are generally selected to minimize the total control delay vehicles experience at an intersection, particularly when the intersection is isolated or undersaturated. However, in practice, there are many other potential objectives that might be considered in signal timing design, including: total passenger delay, pedestrian delays, delay inequity among competing movements, total number of stopping maneuvers, among others. These objectives do not tend to share the same relationships with signal timing plans and some of these objectives may be in direct conflict. The research proposes the use of a new multi-objective optimization (MOO) visualization technique—the mosaic plot—to easily quantify and identify significant tradeoffs between competing objectives using the set of Pareto optimal solutions that are normally provided by MOO algorithms. Using this tool, methods are also proposed to identify and remove potentially redundant or unnecessary objectives that do not have any significant tradeoffs with others in an effort to reduce problem dimensionality. Since MOO procedures will still be needed if more than one objective remains and MOO algorithms generally provide a set of candidate solutions instead of a single final solution, two methods are proposed to rank the set of Pareto optimal solutions based on how well they balance between the competing objectives to provide a final recommendation. These methods rely on converting the objectives to dimensionless values based on the optimal value for each specific objectives, which allows for direct comparison between and weighting of each. The proposed methods are demonstrated using a simple numerical example of an undersaturated intersection where all objectives can be analytically obtained. However, they can be readily applied to other signal timing problems where objectives can be obtained using simulation outputs to help identify the signal timing plan that provides the most reasonable tradeoff between competing objectives.