基于DSP的电源控制系统的软硬件开发

介绍了一种基于DSP的逆变电源控制系统,详细阐述了系统组成结构和软硬件设计.该系统采用TMS320F2812作为主控制器,最大程度的减少了硬件电路的搭建,实现了对逆变电源的数字控制.实验结果证明,该系统具有良好的稳压功能,既能满足一定控制精度要求,又能满足实时性要求,可以很好的控制115V/400Hz逆变电源的输出.     

嵌入式多媒体播放器USB驱动程序设计

本文首先从基于TI DM320的PMP(Portable Multimedia Player,便携式多媒体播放器)解决方案入手,分析了该方案的软、硬件体系框架.接着,仔细研究了嵌入式Linux.然后,以TI DM320平台为例,探讨了嵌入式Linux驱动程序的设计.同时,设计了PMP USB的驱动程序.     

无刷直流电机控制系统的DSP设计方案

为了提高无刷直流电机的控制效果,以典型微控制器TMS320LF2407A为核心,设计了基于DSP的电机控制系统,给出了控制系统硬件设计方案,包括电源管理、驱动电路、串行通讯等模块.该方案电路简单,成本低,可靠性高,具有较好的应用价值.     

Defect Prediction Using Akaike and Bayesian Information Criterion

Data available in software engineering for many applications contains variability and it is not possible to say which variable helps in the process of the prediction. Most of the work present in software defect prediction is focused on the selection of best prediction techniques. For this purpose, deep learning and ensemble models have shown promising results. In contrast, there are very few researches that deals with cleaning the training data and selection of best parameter values from the data. Sometimes data available for training the models have high variability and this variability may cause a decrease in model accuracy. To deal with this problem we used the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) for selection of the best variables to train the model. A simple ANN model with one input, one output and two hidden layers was used for the training instead of a very deep and complex model. AIC and BIC values are calculated and combination for minimum AIC and BIC values to be selected for the best model. At first, variables were narrowed down to a smaller number using correlation values. Then subsets for all the possible variable combinations were formed. In the end, an artificial neural network (ANN) model was trained for each subset and the best model was selected on the basis of the smallest AIC and BIC value. It was found that combination of only two variables’ ns and entropy are best for software defect prediction as it gives minimum AIC and BIC values. While, nm and npt is the worst combination and gives maximum AIC and BIC values.     

基于TMS320F2812的采煤机电动机保护控制模块

为了对采煤机电动机进行有效的在线监测和故障早期诊断,设计了一种基于TMS320F2812的采煤机电动机保护控制模块,介绍了该模块的硬件电路和软件设计。该模块可以实时监测采煤机电动机的运行状态,实现过热、过载、短路、缺相保护功能;同时可对采煤机电动机运行电流谐波进行分析,实现定子、转子故障自诊断功能。井下试验结果表明,该模块可靠性高、实时性强。     

基于DSP无轴承永磁同步电机控制系统设计

为了控制无轴承永磁同步电机的旋转和转子的稳定悬浮,设计出了以TMS320LF2407A为微处理器核心的无轴承永磁同步电机控制系统,充分利用TMS320LF2407A的中断系统设计出能同时控制电机电磁转矩和径向力的软件模块,利用DSP的QEP模块和光电编码器的复位中断CAP6INT实现电机位置的准确检测.最后通过试验测试控制系统输出的转矩绕组和径向力绕组的指令电流波,验证了软件系统设计的实时性和准确性,证明其能满足无轴承永磁同步电机的旋转和稳定悬浮的要求.     

接触网测试仪显示设计

中铁路接触网测试仪是基于TI公司的TMS320F2812数字信号处理芯片的检测系统。结合F2812本身强大的功能,搭配松下公司生产的型号为LTM024D250的液晶,提供实现检测系统的实时工作状态显示——采样数据、波形、设备号等,给现场检测人员提供直观的显示。     

基于TMS320C5402的语音信号压缩存储系统设计

根据TMS320C5402的特点,提出了采用G.711语音编解码算法设计的语音压缩系统,给出了系统的硬件结构和软件流程及A/D、D/A模块与TMS320C5402接口电路的设计方法。该系统具有很高的实时性和实用性。     

Finding an Euclidean anti--centrum location of a set of points

An obnoxious facility is to be located inside a polygonal region of the plane, maximizing the sum of the k smallest weighted Euclidean distances to n given points, each protected by some polygonal forbidden region. For the unweighted case and k fixed an O(n²logn) time algorithm is presented. For the weighted case a thorough study of the relevant structure of the multiplicatively weighted order-k-Voronoi diagram leads to the design of an O(kn³+n³logn) time algorithm for finding an optimal solution to the anti-t-centrum problem for every t=1,…,k, simultaneously.     

基于TMS320F2812的太阳跟踪器设计

采用传感器和太阳位置计算相结合的方法,设计了基于TI公司的TMS320F2812的高精度太阳跟踪器。一方面可以防止较大误差积累,另一方面可以避免光线、天气情况的影响,跟踪精度得到了较大提高,能够很好地应用于光伏发电系统实现对太阳的精确跟踪。