基于RS-485的哨位报警广播系统设计

对基于RS-485总线的哨位报警广播系统进行了介绍,描述了其系统结构、原理及实现。根据实际需求,本系统采用RS-845总线技术,构成了主从式的报警广播网络,实现了四色报警联动。系统布线简单,抗干扰能力强,满足哨位执勤的实际需求。     

基于VXI总线的飞机供电系统参数测试处理系统的实现

介绍了一种基于VXIbus的飞机供电参数的自动测试处理系统的设计和实现，系统设计中采用符合VXI部总线规范的仪器模块，实现多通道高精度及快速的数据采集，采集方式包括并行和巡回检测两种，采用即插即用结构功能扩展非常方便。在HPVEE5．0软件平台下，利用软前面板技术可用交互方式控制VXI仪器模块，用户界面直观明了，大大简化了VXI仪器的操作使用，根据相关标准采用VC^ 和HPVEE相结合的方法设计了数据处理软件，建立了动态链接库，通过单相交流电源系统的测试试验，表明系统性能先进，稳定可靠，测试精度高，具有广泛的应用前景。     

客车骨架结构有限元分析

研究用有限元法对半承载式客车车身刚度、强度、振动特性进行分析的方法,为设计的正确性提供有价值的理论依据和校核,并以6115型客车为对象进行静力学和振动特性分析。     

并行多种群自适应遗传算法在COW集群上的实现

为改善标准遗传算法的求解效率,提出一种基于6模糊控制器的并行多种群自适应遗传算法。利用MPI(Messagepassinginterface)技术建立了一个COW(Clusterofworkstation)集群,将算法在该硬件平台上进行了实现。3机COW集群的仿真实验结果在演示算法设计可行性的同时,表明该算法的求解效率明显优于用于对照的单种群算法,具有在解决组合优化问题上广泛应用的可能。本文还对影响并行算法的参数进行了探讨。     

多电飞机配电系统TTP/C总线应用技术研究

C类时间触发协议(Time triggered protocol/class C,TTP/C)总线具有安全性高、实时性好和传输速度快的优点,本文提出将TTP/C总线应用于多电飞机配电系统中。首先分析了多电飞机分布式自动配电系统的结构,以及TTP/C总线架构和特点。然后提出了针对飞机配电系统的通讯网络,利用动态链接库分别实现C语言和LabVIEW语言环境下的通讯软件编程。接着给出,偏移地址选择方法决定数据来源走向,提出数据空间转换和格式转换方法提高通讯效率和可靠性。最后经过系统试验表明,该应用技术能够实现飞机配电系统中的TTP/C总线应用,满足系统通讯要求,提高多电飞机通讯系统的可靠性和通讯速度。     

基于时间触发的精简串行总线技术

针对事件触发机制应用到小型分布式测试系统中,存在控制命令复杂、需要主控制器的不足,提出一种基于时间触发的精简串行总线技术。详细分析总线系统的组成、信号线定义、总线系统基本特征、数据格式以及总线系统的时分多路访问(Time division multiple access,TDMA)通信控制机制。重点介绍时间触发功能的TDMA时序管理机的实现方法,进行基于硬件描述语言Verilog-hdl的软件设计,并进行仿真。仿真结果显示,TDMA时序管理机可实现系统多节点时槽分配管理功能,采用该时序管理机有利于实现基于时间触发的总线控制方案、构建小型分布式测试系统。     

基于ISA总线的数据采集板的设计

简要介绍 ISA总线接口 ,并从硬件设计和逻辑设计方面详细阐述一种基于 CPLD芯片 isp L SI5 5 12 VA的 ISA总线接口通信协议的和 A/ D采集的实现。     

GDP spatialization in Ningbo City based on NPP/VIIRS night-time light and auxiliary data using random forest regression

Accurate spatial distribution information on gross domestic product (GDP) is of great importance for the analysis of economic development, industrial distribution and urbanization processes. Traditional administrative unit-based GDP statistics cannot depict the detailed spatial differences in GDP within each administrative unit. This paper presents a study of GDP spatialization in Ningbo City, China based on National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL) data and town-level GDP statistical data. The Landsat image, land cover, road network and topographic data were also employed as auxiliary data to derive independent variables for GDP modelling. Multivariate linear regression (MLR) and random forest (RF) regression were used to estimate GDP at the town scale and were assessed by cross-validation. The results show that the RF model achieved significantly higher accuracy, with a mean absolute error (MAE) of 109.46 million China Yuan (CNY)·km⁻² and a determinate coefficient (R² = 0.77) than the MLR model (MAE = 161.8 million CNY·km⁻², R² = 0.59). Meanwhile, by comparing with the estimated GDP data at the county level, the town-level estimated data showed a better performance in mapping GDP distribution (MAE decreased from 115.1 million CNY·km⁻² to 74.8 million CNY·km⁻²). Among all of the independent variables, NTL, land surface temperature (T_s) and plot ratio (PR) showed higher impacts on the GDP estimation accuracy than the other variables. The GDP density map generated by the RF model depicted the detailed spatial distribution of the economy in Ningbo City. By interpreting the spatial distribution of the GDP, we found that the GDP of Ningbo was high in the northeast and low in the southwest and formed continuous clusters in the north. In addition, the GDP of Ningbo also gradually decreased from the urban centre to its surrounding areas. The produced GDP map provides a good reference for the future urban planning and socio-economic development strategies.     

An LMI-based decoupling control for electromagnetic formation flight

Electromagnetic formation flight(EMFF) leverages electromagnetic force to control the relative position of satellites. EMFF offers a promising alternative to traditional propellant-based spacecraft flight formation. This novel strategy is very attractive since it does not consume fuel. Due to the highly coupled nonlinearity of electromagnetic force, it is difficult to individually design a controller for one satellite without considering others, which poses challenges to communications.This paper is devoted to decoupling control of EMFF, including regulations, constraints and controller design. A learning-based adaptive sliding mode decoupling controller is analyzed to illustrate the problem of existing results, and input rate saturation is introduced to guarantee the validity of frequency division technique. Through transformation, the imposed input rate saturation is converted to state and input constraints. A linear matrix inequalities(LMI)-based robust optimal control method can then be used and improved to solve the transformed problem. Simulation results are presented to demonstrate the effectiveness of the proposed decoupling control.     

Improving the estimation of zenith dry tropospheric delays using regional surface meteorological data

Global Navigation Satellite Systems (GNSS) are emerging as possible tools for remote sensing high-resolution atmospheric water vapour that improves weather forecasting through numerical weather prediction models. Nowadays, the GNSS-derived tropospheric zenith total delay (ZTD), comprising zenith dry delay (ZDD) and zenith wet delay (ZWD), is achievable with sub-centimetre accuracy. However, if no representative near-site meteorological information is available, the quality of the ZDD derived from tropospheric models is degraded, leading to inaccurate estimation of the water vapour component ZWD as difference between ZTD and ZDD. On the basis of freely accessible regional surface meteorological data, this paper proposes a height-dependent linear correction model for a priori ZDD. By applying the ordinary least-squares estimation (OLSE), bootstrapping (BOOT), and leave-one-out cross-validation (CROS) methods, the model parameters are estimated and analysed with respect to outlier detection. The model validation is carried out using GNSS stations with near-site meteorological measurements. The results verify the efficiency of the proposed ZDD correction model, showing a significant reduction in the mean bias from several centimetres to about 5 mm. The OLSE method enables a fast computation, while the CROS procedure allows for outlier detection. All the three methods produce consistent results after outlier elimination, which improves the regression quality by about 20% and the model accuracy by up to 30%.