基于TD-SCDMA的煤矿智能电力故障检测与分析系统

针对煤矿井下供电设备故障给煤矿安全生产带来很大隐患的问题,提出了一种基于TD-SCDMA技术的煤矿智能电力故障检测与分析系统。该系统通过供电检测采集系统实时采集各段母线电压、各分支电流、功率、断路器状态以及故障信息,然后通过TD-SCDMA/工业以太网络支撑系统将煤矿供配电系统各设备运行状态、运行参数、故障信息传输到智能电力故障分析系统,完成煤矿供配电系统的信息加工、分析和故障诊断与处理。应用结果表明,该系统提高了供电可靠性,为煤矿的安全生产提供了保障。     

双向全桥DC-DC变换器单移相闭环控制研究

针对基于传统单移相控制的双向全桥DC-DC变换器存在效率低的问题,提出了一种基于单移相闭环控制的双向全桥DC-DC变换器设计方案;分析了双向全桥DC-DC变换器稳态特性,详细介绍了基于单移相闭环控制的双向全桥DC-DC变换器的建模实现。仿真与实验结果表明,基于单移相闭环控制的双向全桥DC-DC变换器效率高、损耗小。     

一种开关磁阻电动机功率变换器故障诊断方法

针对现有开关磁阻电动机功率变换器故障诊断方法存在可靠性不高等问题,提出了一种新型的功率管故障诊断方法。该方法以不对称半桥型功率变换器主电路为研究对象,以常见的功率管开路和短路2种故障情况为诊断对象,通过比较母线电流估算值和实测值来判断故障,结合故障相绕组电流实现故障相的识别,必要时通过中断测试来确定故障点。选取电动机空载、低速度和高速度运行等较难实现故障诊断的工况进行了试验分析,结果表明,该方法均能完成故障类型的定性及故障点的准确定位。     

PWM整流器保持高功率因数运行的方法研究

针对煤矿井下电压波动严重时影响稳压电源的单位功率因数等问题,提出采用可变输出直流电压法来控制PWM整流器的直流侧电压,以保证PWM整流器处于高功率因数运行的工作状态;详细分析了直流侧电压的选取及交流侧输入电压大范围波动对交流侧输入电流及功率因数的影响,介绍了可变输出直流电压法的控制原则及软件实现。试验结果表明,在电压波动情况下,可变输出直流电压法不仅可使PWM整流器系统稳定,而且可以保持整流器的高功率因数运行状态。     

供电企业信息作业风险评估研究

在深入研究事故致因理论、事故风险管理和供电企业生产作业风险管理的基础上,提出了供电企业信息作业风险评估的模型和方法。有助于供电企业建立一套基于风险管理的信息作业指导书,为信息运维人员提供安全作业操作规范,减少安全事故的发生。     

基于分布式计算的电网运行可靠性评估算法研究

针对电网运行可靠性评估计算量大,但又要求计算时间短的问题,提出了一种基于分布式计算的电网运行可靠性评估算法。该算法采用改进的状态选择和分析方案,解决了计算终端间随机数序列的关联性问题,有效地降低了通信量,提高了计算速度。基于该算法编制的评估软件已通过RTS-24系统和某省级电网的实际运行测试,测试结果表明,该算法不仅能够有效评估电网运行可靠性,而且计算速度随计算终端数增加呈一定倍数提高。     

多路输出反激式开关电源的改进与实现

针对传统开关电源存在的控制芯片供电方式耗能较大、反馈电路光耦有效输入电流范围窄两个问题,对传统电源电路进行了改进,设计并实现了一款性能优良的48V转+5V、±15V,输出功率25W的三路输出反激式开关电源。样机输出电压精度为0.2%(+5V)、0.53%(+15V)、0.6%(-15V),输出电压纹波为20mV(+5V)、50mV(+15V)、60mV(-15V),电压精度和纹波率均满足小于1%的要求;测试表明:该电源性能优良,具有效率高,稳压精度高,负载调整率高等优点,有很高的生产应用价值。     

椭圆曲线密码中抗功耗分析攻击的标量乘改进方案

椭圆曲线标量乘法运算是椭圆曲线密码(ECC)体制中最主要的计算过程,标量乘法的效率和安全性一直是研究的热点。针对椭圆曲线标量乘运算计算量大且易受功耗分析攻击的问题,提出了一种抗功耗分析攻击的快速滑动窗口算法,在雅可比和仿射混合坐标系下采用有符号滑动窗口算法实现椭圆曲线标量乘计算,并采用随机化密钥方法抵抗功耗分析攻击。与二进制展开法、密钥分解法相比的结果表明,新设计的有符号滑动窗口标量乘算法计算效率、抗攻击性能有明显提高。     

Multi-channel power allocation based on market competitive equilibrium in cognitive radio networks

Cognitive radios such as intelligent phones and Bluetooth devices have been considered essential goods in next-generation communication systems.Such devices will have to share the same frequency band owing to the limited bandwidth resource.To improve spectrum efciency,we formulate multi-channel power allocation as a market competitive equilibrium(CE)problem,and prove that its solution exists and is unique under the condition of weak interference.We then propose two distributed power allocation algorithms achieving CE,namely the fast convergent power allocation algorithm(FCPAA)and the social-fairness-aware FCPAA(SFAF).Theoretical analysis and simulation results demonstrate that the proposed algorithms lead to better system performance in terms of the guaranteed interference temperature constraint using the price mechanism instead of a strategy based on the Nash equilibrium.Moreover,it is shown that the FCPAA maximizes total utility,and converges more quickly than the method addressed in prior research with the help of improved round-robin rules.However,the FCPAA cannot ensure the same social fairness among secondary users as the SFAF scheme in both the non-fading channel and Rayleigh fading channel;the SFAF balances the individual utility by adjusting each user’s budget at the expense of a small quantity of system total throughput.     

Correlations between characteristics of maximum influence and degree distributions in software networks

Software systems can be represented as complex networks and their artificial nature can be investigated with approaches developed in network analysis.Influence maximization has been successfully applied on software networks to identify the important nodes that have the maximum influence on the other parts.However,research is open to study the effects of network fabric on the influence behavior of the highly influential nodes.In this paper,we construct class dependence graph(CDG)networks based on eight practical Java software systems,and apply the procedure of influence maximization to study empirically the correlations between the characteristics of maximum influence and the degree distributions in the software networks.We demonstrate that the artificial nature of CDG networks is reflected partly from the scale free behavior:the in-degree distribution follows power law,and the out-degree distribution is lognormal.For the influence behavior,the expected influence spread of the maximum influence set identified by the greedy method correlates significantly with the degree distributions.In addition,the identified influence set contains influential classes that are complex in both the number of methods and the lines of code(LOC).For the applications in software engineering,the results provide possibilities of new approaches in designing optimization procedures of software systems.