集成电路测试系统总定时精度自动校准程序设计

在高速集成电路测试应用中,当集成电路测试系统驱动或测量某一信号时,其驱动沿或比较沿与预期时间产生1ns的偏差都将导致整个测试时序严重偏离,使测试结果失去意义。系统总定时精度(OTA)就是反映测试系统提供的信号驱动或比较沿是否在预期的时间范围内,各信号之间的相对时间是否准确的关键时间参量,必须进行校准保证其溯源性。论文以V93000集成电路测试系统为例,介绍了集成电路测试系统总定时精度自动校准程序的设计方法。     

电热水器智能化系统设计

本文主要介绍了电热水器的定时保温控制系统的设计.根据系统的特点,设计分为时钟定时部分、温度采集部分和电源控制部分.本设计的时钟设定及显示功能利用PIC16F877A芯片来完成,温度采集部分由温度传感器DS18B20来完成,电源控制部分由继电器来完成,同时利用PIC 16F877A的RB端口来控制电热水器开关及输入调整时间和温度.     

Achieving accurate and context‐sensitive timing for code optimization

Key computational kernels must run near their peak efficiency for most high‐performance computing (HPC) applications. Getting this level of efficiency has always required extensive tuning of the kernel on a particular platform of interest. The success or failure of an optimization is usually measured by invoking a timer. Understanding how to build reliable and context‐sensitive timers is one of the most neglected areas in HPC, and this results in a host of HPC software that looks good when reported in the papers, but delivers only a fraction of the reported performance when used by actual HPC applications. In this paper, we motivate the importance of timer design and then discuss the techniques and methodologies we have developed in order to accurately time HPC kernel routines for our well‐known empirical tuning framework, ATLAS. Copyright © 2008 John Wiley & Sons, Ltd.     

Modular multi-channel data acquisition systems

A flexible approach to complexity-reduced multi-channel data acquisition from a large quantity of sensors, essential for connecting computers with real world objects, is discussed and the obtained experience in this area is summarized. Data acquisition from wideband, event timing, and large distributed clusters of signal sources are discussed with emphasis on methods and algorithms providing for data gathering from large sensor systems. We discuss special signal digitizing techniques, including pseudorandomized multiplexing, time-to-digital conversions, and signal sample value-taking at time instants when the input signal crosses a sinusoidal reference function. The versatility of the data acquisition systems is achieved by using modular system design. To achieve the maximum from the suggested data acquisition technology, the acquired data processing is based on the theory of digital alias-free signal processing. The text was submitted by the authors in English.     

基于特征参数的柴油机喷油正时状态诊断

燃油供给系统是柴油机最重要的子系统之一,它的性能的好坏直接影响到混合气的形成过程和发动机的动力性、起动性、噪声及环境污染等性能。柴油机喷油正时与否直接决定供油系统能否正常工作,针对柴油机在不同喷油状态下的压力波动变化,采用外卡测量并对压力信号进行预处理和二次处理,从中提取诊断特征值,从而给出不同工况的诊断结果,由于油压波形信号重复性较好,各缸同一工作段的某些幅域参数变化不大,因此,幅域参数作为诊断供油系统喷油状态的方法是可行的、有效的。     

Windows异步串行通信编程纵横

从实践和理论角度汇总了Windows下异步串行通信编程的基本规律和常见方法,指出了各种编程方法的优势和不足,重点阐述了如何扬长避短、综合应用各种方法编程实现可靠而高效的串行数据通信,突出说明了怎样使用“特定通信协议和定时机制、多线程优化和WinAPI”的最优串行编程的数据接收过程实现。     

计及多能流运行时序性的电-气互联系统协同状态估计

电-气互联综合能源系统可灵活实现多区域能源交互,但其多能流子系统存在的信息交互壁垒、量测延迟等时序不统一因素会给系统精准监测与调度带来不利影响。针对多能流子系统不同的运行时间尺度,构建计及统一时间尺度的顺序协同估计框架,并考虑多源量测设备采样周期的延迟问题,将量测时延融合思想引入估计框架中以矫正多源量测数据的时序不同步。提出基于改进卡尔曼滤波的综合能源系统实时估计算法,通过引入基于改进交替投影的对称正定理论,避免实时估计过程中因误差传播出现非正定导致的估计失败问题。仿真结果与对比分析验证了所提协同状态估计策略能够有效实现对电-气互联综合能源系统的在线精准监控,且估计结果具备更强的数值稳定性。     

FBMC系统改进序列算法的定时同步技术

为提高滤波器组多载波（Filter Bank Multicarrier,FBMC）系统在低信噪比下的定时同步准确率和抗频偏性能,基于FBMC系统与正交频分复用（Orthogonal Frequency Division Multiple,OFDM）系统的相似性,对OFDM系统定时同步中的Park测度函数进行改进并引入到FBMC系统中。利用共轭对称结构能够提高定时精度和加权处理能够更好地抵抗频偏影响的特点设计同步序列,进行共轭对称和加权处理。仿真结果表明,基于改进序列的Park算法相较共轭对称序列的TR1算法,其信噪比提前3 dB达到了100%定时准确率,实现了低信噪比下的高精度定时同步,且具有更强的抗频偏性能;相较原Park算法,相同信噪比下,改进序列的Park算法的频偏均方差（Mean Square Error,MSE)也小于原Park算法的频偏MSE,抗频偏性能表现更优。     

基于FPGA的多通道雷达数据回放系统设计

为解决雷达实时信号处理功能及性能有效验证问题,文中设计并实现了一种宽窄带一体化、多通道雷达数据回放系统。该系统按雷达工作的时序和数据率将雷达回波数据发送至实时信号处理系统,从而对目标跟踪场景进行复现,实现雷达实时信号处理功能及性能的有效验证。系统硬件平台由磁盘阵列服务器与两块PCIe光纤板组成。基于Xilinx系列产品,结合系统特点对PCIe DMA控制流程及响应机制做进一步调整,实现了服务器到光纤板的雷达回波数据高速批量传输。根据雷达工作机制及回波数据结构,设计FPGA回放控制状态机及相关功能模块,严格按照雷达工作的时序和数据率使雷达回波数据由光纤板传输至实时处理系统。分别设计软件同步控制方法和硬件同步控制方法,保证多板卡数据回放的同步性。测试结果表明,该系统实现了宽、窄带雷达回波数据的板间同步回放,各数据类型分别支持6路并行数据通道,数据回放峰值速率可达1 920 MB·s^-1。文中系统可依托雷达原有硬件平台实现,无需增设板卡和线缆,具有良好的集成性与通用性,目前已被应用于某多功能相控阵雷达中。     

Combustion timing control of HCCI engine based on NNPC and Elman-NN model under complex conditions

Homogeneous Charge Compression Ignition (HCCI) combines the characteristics of gasoline engine and diesel engine with high thermal efficiency and low emissions. However, since there is no direct initiator of combustion, it is difficult to control the combustion timing in HCCI engines under complex working conditions. In this paper, Neural Network Predictive Control (NNPC) for combustion timing of the HCCI engine is designed and implemented. First, the black box model based on Elman neural network is designed and developed to estimate the combustion timing. The fuel equivalence ratio, intake valve closing timing, intake manifold temperature, intake manifold gas pressure, and engine speed are chosen as the system inputs. Then, a NNPC controller is designed to control combustion timing by controlling the intake valve closing timing. Simulation results show that the Elman neural network black box model is capable of estimating the HCCI engine combustion timing. In addition, regardless of whether the HCCI engine is in constant or complex condition, the designed NNPC controller is capable of keeping the combustion timing within the ideal range. In particular, under New European Driving Cycle (NEDC) working conditions, the maximum overshoot of the controller is 28.95% and the average error is 1.03 crank angle degree. It is concluded that the controller has good adaptability and robustness.