收发同体型超声测距系统设计

介绍了一种收发同体型超声测距系统。该系统由发射电路、前置放大电路、滤波电路、AGC、整形电路和单片机控制器等组成。前置放大器由音频功放LM386组成。另外,对数据的采集和处理采用了反射波峰值检测法,取得了良好的效果。     

基于RBF的传感器在线故障诊断和信号恢复

介绍利用径向基神经网络构造了一种在线故障诊断及信号恢复方法,给出了网络的连接结构和学习算法。采用RBF神经网络进行传感器在线故障诊断和信号恢复,其仿真结果表明,该方法具有收敛速度快、信号恢复准确度高、泛化能力强的特点,且可以诊断多种复杂工作系统的传感器在线故障信号,同时进行信号的恢复。实现传感器状态监测、故障诊断、分离和信号恢复。     

Development of a false alarm free, Advanced Loose Parts Monitoring System (ALPS)

An Advanced Loose Parts Monitoring System (its acronym is ALPS) has been developed and installed on each unit of the Paks Nuclear Power Plant, Hungary. ALPS uses sophisticated methods to identify the events hidden in the quite extensive background noise of nuclear power plants. A classification algorithm based on an expert system, which is trained during the start-up period of each fuel cycle, helps to improve the false alarm rate. Thus the false alarm rate was reduced to a minimum, statistically below 1%. In practice, even the remaining “false alarms” were identified to be originating from other noise sources using ALPS. The main principles of ALPS are presented. It is demonstrated, that even weak signals, comparable with the resolution of the analog-digital board, i.e. comparable with detection noises, can be identified at high certainty. Other events like vibration of the shaft of motor operated isolating valves have been identified by ALPS. Furthermore, experiences gained during the installation period are also discussed.     

Development of microphone leak detection technology on Fugen NPP

A method of leak detection, based on high-temperature resistant microphones, was originally developed in JNC to detect leakages with flow rates from 1 m³/h to 500m³/h. The development performed on Fugen is focused on detection of a small leakage at an early stage. Specifically, for the inlet feeder pipes the leak rate of 0.2gpm (0.046m³/h) has been chosen as a target detection capability. Evaluation of detection sensitivity was carried out in order to check the capability of the method to satisfy this requirement. The possibility of detecting and locating a small leakage has been demonstrated through the research.     

堆泵浦3He-Ar-Xe激光体系小信号增益与效率实验研究

介绍了CFBR-Ⅱ堆泵浦3He-Ar-Xe体系1.73μm波长激光小信号增益和泵浦效率的实验研究.在脉冲峰热中子注量率为6.9×1014cm-2.s-1、3He、Ar、Xe气体的比例为80.219.30.5,总压强为8.3×104Pa时,采用透射率从1.7%到10%的6个谐振腔输出镜均获得了激光输出.在谐振腔输出镜透射率为7%时,得到了激光脉冲峰功率为45mW,其对应的激光泵浦效率为1%.在此基础上,利用Rigroa分析方法拟合出3He-Ar-Xe体系激光的小信号增益为0.24%/cm,饱和光强为36W/cm2.     

校园电缆电视系统设计

介绍了山东建筑工程学院校园电缆电视系统的设计原理。比较详细地介绍了利用对线路放大器电源的控制达到同时控制学生宿舍电视机电源与电视信号的方法 ,同时还介绍了学生宿舍能收看所有频道的“正常接收”与所有频道同时播送一个节目的“强制接收”互相切换的方法。并且给出了相关设备的内部结构和工作原理。     

基于Wigner-Hough变换的多分量LFM信号 检测及离散计算方法

Wigner-Hough变换对LFM信号有压缩和聚焦的作用,这种作用的又具有阈值特性,本文简述Wigner-Hough变换的方法及对该方法的评价.重点讨论Wigner-Hough变换的离散计算,提出了一种对Wigner变换的结果再进行Hough变换的类似二维搜索的离散计算方法.     

基于TCP/IP数传技术的通用信号处理系统显控平台设计

针对通用信号处理系统的显控功能需求，研究了一种基于TCP，IP数据传输技术、VxWorks嵌入式技术的显控平台设计方法。该平台采用模块化设计，可对多通道数据进行时频分析。对显控平台的功能特点进行了分析，对基于TCP/IP协议与VxWorks进行数据传输的方法进行了重点研究．时平台的功能进行了实验验证。     

低频宽带发射信号的DSP处理

介绍了在数字信号集成开发环境（CODE COMPOSER STUDIO）下进行DSP软件开发的过程，详细阐述了利用TMS320C5410数字信号处理芯片，通过C语言编程实现低频宽带发射信号仿真的设计流程，这一设计的实现，不仅达到了预定的技术标准，而且突破了以硬件电路产生振荡和调制，由功放发出带载频信号的传统方法；克服了硬件电路难调整，不稳定的缺点，实现了通信过程中发射部分的数字化。     

Modeling power and intermodulation behavior of microwave transistors with unified small‐signal/large‐signal neural network models

This article presents a detailed procedure to learn a nonlinear model and its derivatives to as many orders as desired with multilayer perceptron (MLP) neural networks. A modular neural network modeling a nonlinear function and its derivatives is introduced. The method has been used for the extraction of the large‐signal model of a power MESFET device, modeling the nonlinear relationship of drain‐source current I_ds as well as gate and drain charge Q_g and Q_d with respect to intrinsic voltages V_gs and V_ds over the whole operational bias region. The neural models have been implemented into a user‐defined nonlinear model of a commercial microwave simulator to predict output power performance as well as intermodulation distortion. The accuracy of the device model is verified by harmonic load‐pull measurements. This neural network approach has demonstrated to predict nonlinear behavior with enough accuracy even if based only on first‐order derivative information. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 276–284, 2003.