金属氧化物半导体场效应晶体管中总剂量效应导致的阈值电压漂移研究现状

为了研发可用于核与辐射应急响应与准备的机器人,对比了多种具有不同结构和生产工艺的金属氧化物半导体场效应晶体管(MOSFET)由于总剂量效应(TID)导致的阈值电压漂移(ΔV_th)。注意到了栅宽和栅长对器件耐辐射能力的影响在体CMOS器件和纳米线(NW)MOSFET器件之间、高的和低的工艺节点之间的不同,并从辐射诱导的窄通道效应(RINCE)和辐射诱导的短通道效应(RISCE)两方面解释了这种区别的原因。发现近年来前沿的一些研究在考虑辐射效应时,修正了负偏压不稳定性(NBTI)的影响。并讨论了几种新型器件包括锗沟道、氮化镓沟道管和具有特殊几何布局的晶体管。此外,介绍了计算机辅助设计技术(TCAD)在几种新型场效应管的机理研究和建模验证中的应用。     

采用轮廓特征匹配的红外-可见光视频自动配准

为了精确地配准近平面场景下的红外-可见光视频序列,本文提出了一种基于轮廓特征匹配的自动配准方法,通过迭代匹配目标轮廓特征来解决异源图像中配准特征的提取和匹配难题。首先,采用运动目标检测技术获取目标轮廓,并由曲率尺度空间(CSS)角点检测算法提取轮廓特征点。此后,建立全局形状上下文描述子和局部边缘方向直方图描述子描述特征,从而实现可靠的特征匹配。来自不同时刻的匹配点对被保存在一个基于高斯距离准则的特征匹配库中。最后,为了克服近平面场景中目标深度变化的影响,本文结合前景样本随机抽样策略计算配准矩阵的损失函数,完成对全局配准矩阵的更新。在LITIV数据库上对方法进行实验验证,结果表明本文方法的配准精度优于当前先进的对比方法,在9个测试视频上的平均重叠率误差仅为0.194,与对比方法相比下降了18.5%。基本满足了近平面场景下红外-可见光视频序列配准的精度要求,且具有较高的鲁棒性。     

基于加权中智C均值算法的变压器故障诊断模型

为提高变压器故障诊断准确度,提出了一种基于加权中智C均值算法的变压器故障诊断方法。该方法利用基于样本相似度的加权方法对样本特征进行加权,再引入中智理论对样本的分布重新分配,建立起基于加权中智C均值算法的变压器故障诊断模型。研究结果表明,该方法不仅弥补了传统FCM相同权重分配的不足,有效提高了故障诊断的准确率,且诊断结果产生的中智点对故障的变化预测具有重要意义。     

分散式风电多点接入协调优化控制策略

针对分散式风电机组并网导致的配电网网损增加、电压稳定性降低等问题,文章提出一种分散式风电并网多点协调双层控制策略。首先,分析了分散式风电多点接入特性,研究分散式风电多点接入后的网损、电压分布和功率因数的关系,并提出最小网损和电压偏差为目标的双层优化控制策略。最后,基于IEEE-33节点进行仿真计算,结果表明,所提多点协调控制策略能够有效降低配电网网损和提升母线电压水平,增加系统的稳定性。与超前功率因数相比,滞后的功率因数能够增大风能消纳能力,提高供电可靠性,减少电压偏移水平。     

Three-phase four-wire shunt active power filter based on the SOGI filter and Lyapunov function for DC bus control

The three-phase four-wire shunt active power filter (SAPF) was developed to suppress the harmonic currents generated by nonlinear loads, and for the compensation of unbalanced nonlinear load currents, reactive power, and the harmonic neutral current. In this work, we consider instantaneous reactive power theory (PQ theory) for reference current identification based on the following two algorithms: the classic low-pass filter (LPF) and the second-order generalized integrator (SOGI) filter. Furthermore, since an important process in SAPF control is the regulation of the DC bus voltage at the capacitor, a new controller based on the Lyapunov function is also proposed. A complete simulation of the resultant active filtering system confirms its validity, which uses the SOGI filter to extract the reference currents from the distorted line currents, compared with the traditional PQ theory based on LPF. In addition, the simulation performed also demonstrates the superiority of the proposed approach, for DC bus voltage control based on the Lyapunov function, compared with the traditional proportional-integral (PI) controller. Both novel approaches contribute towards an improvement in the overall performance of the system, which consists of a small rise and settling time, a very low or nonexistent overshoot, and the minimization of the total harmonic distortion (THD).     

高大软岩边坡下开采程序研究

结合胜利煤田发生大型滑坡的露天矿地质赋存条件，以高大软岩边坡条件下松散物料压覆的煤炭资源安全高效回收为目标，提出采用“横采内排-尾随压脚”的开采程序方案将工作线从直线型变为“Π”字型。从地表水与地下水防治、边坡安全监测等方面提出了保证工程顺利实施的安全保障措施。计算分析了采用“横采内排-尾随压脚”开采程序方案的可观资源回收量及减少运距和提升高度带来的经济效益，同时对矿山实现可持续发展和安全开采的价值进行了预测。     

阳极导电材料对铁钨锡合金粉电解铁的影响

研究阳极导电材料碳素钢、316L不锈钢、铅钙合金、石墨、钛涂钌板、钛板和铜板在硫酸盐和氯盐体系中对铁钨锡合金粉电解铁的影响。结果表明:电解24 h,上述阳极导电材料在氯盐中的阴极电流效率为90%、90%、66%、66%、54%、49%、33%,在硫酸盐中的阴极电流效率为90%、87%、82%、81%、73%、68%、54%。槽电压均逐渐升高,在氯盐体系中,石墨、铅钙合金、钛涂钌板和钛板作阳极导电材料时,电解液pH逐渐降低;碳素钢、316L不锈钢和铜板作阳极导电材料时,电解液pH逐渐升高。在硫酸盐体系中,铜板和碳素钢作阳极导电材料时,电解液pH基本不变;316L不锈钢作阳极导电材料时,pH逐渐升高;铅钙合金、石墨和钛板作阳极导电材料时,pH先升高后降低。基于槽电压、阴极电流效率,选择适宜的电解体系为硫酸盐体系,该体系中适宜的阳极导电材料为铅钙合金。     

Modeling of sequence length distribution for olefin copolymerization with vanadium-based catalyst

Some thermodynamic and mechanical properties of a polyolefin, such as the melting temperature and the rigidity, are dependent on the nature of its sequence distribution. Accurate modeling of sequence length distribution (SLD) is important in precisely tuning and optimizing the properties of polymers produced. In this article, we proposed a model to predict the molecular weight distribution (MWD) and SLD for olefin copolymerization with vanadium-based catalyst. Due to the 2,1-insertion of α-olefin with vanadium-based catalyst, the SLD is expressed by uninterrupted methylene sequence distribution instead of conventional triad sequence distribution. To obtain a reliable model, parameter estimation with experimental data is first conducted. The SLD model along with the estimated kinetic parameters can be used to predict unmeasurable sequence length fraction. For the experimental conditions studied, the average methylene sequence length is predicted to change from 10 to 4 units as the propylene/ethylene mole feed ratio increases from 1.1 to 3.4.     

State of charge estimation for lithium-ion battery based on an intelligent adaptive unscented Kalman filter

Adaptive unscented Kalman filter (AUKF) has been widely used for state of charge (SOC) estimation of lithium-ion battery. The noise covariance of the conventional AUKF method is updated based on the innovation covariance matrix (ICM), which is estimated using the error innovation sequence (EIS). However, the distribution of EIS changes due to the time-varying noise, load current dynamics and modelling error, which will lead to inaccurate ICM estimation. Therefore, an intelligent adaptive unscented Kalman filter (IAUKF) method is proposed to detect the distribution change of EIS. Then, the ICM is estimated based on the EIS after the distribution change. Results show that the IAUKF method can improve SOC estimation accuracy significantly. Compared with that of the AUKF method, the root mean squared error and the mean absolute error of SOC based on the IAUKF method decrease by 43.70% and 72.37% under random walk discharge condition, respectively. In addition, the computation time of the IAUKF method slightly increases by 6.27% compared with that of AUKF method. Finally, the effect of initial parameters on the SOC estimation accuracy was analysed. The results indicate that proper algorithm tuning, such as initial window length of EIS for ICM update and the threshold value, can further improve the SOC accuracy based on the proposed IAUKF method. The proposed IAUKF method also shows high robustness against initial measurement noise covariance.     

Maximum power point tracking supported proton exchange membrane fuel cell based intelligent dynamic voltage restorer

In modern era, electrical power utilities are more concerned about power quality. In this endeavour, dynamic voltage restorer (DVR) provides adequate support to the system. Accordingly, the present work illustrates intelligent hybrid control mechanism for DVR. Artificial neural network (ANN) is incorporated to obtain real-time optimal gains under distinct voltage situations. Closed loop type 2 fuzzy logic (CLT2-FL) is also realized in order to assist the ANN supported unit concomitantly. In order to enhance the potential of the present DVR, a CLT2-FL controlled maximum power point tracking (MPPT) based proton exchange membrane fuel cell arrangement is also explored in the present study. CLT2-FL module is adopted in DC-DC converter topology to provide simultaneous supply to the loads at different and regulated voltage levels. Consequently, the results are evaluated and compared to the state-of-the-arts which unveil the efficacy of the implemented controller against the oddity seen in the voltage waveform, thereby, exhibiting better voltage regulation and less harmonics. The effectiveness of the implemented MPPT unit from the viewpoints of convergence speed and oscillations is also established.