燃料电池内阻在线测试系统研究

内阻是反应燃料电池性能的重要指标,设计燃料电池内阻在线测试系统具有重要意义.但燃料电池内阻具有明显的非线性和时变特性,一般难以精确测量.为了解决这个问题,本文在对燃料电池内阻进行分析的基础上,结合电化学阻抗谱测试思想,提出了一种改进的燃料电池欧姆内阻在线测试法--交流变频调幅测量法,并基于高性能数字信号处理器设计了测试系统硬件电路和软件,得到了较好的测量效果.     

灰色理论在故障诊断参量有效性分析中的应用

为了选取合理的电气设备监测和诊断参量,将灰关联分析应用于参量的分析中.先确定参考序列和比较序列,计算关联度,然后确定合理的参量.并以氧化锌避雷器(MOA)的绝缘诊断为实例,经计算比较表明,采用阻性泄漏电流基波峰值作为参量来监测和诊断MOA的绝缘状态是合理的.     

关于Hadamard矩阵结构特点之分析

从具体结构上对Hadamard矩阵作出较为详细的分析,进而得到若干有利于更具体地把握其结构特点的结论.     

一种通用的分布式实时数据显控方法

提出了基于控制文件的通用分布式实时数据显控方法,给出了其总体逻辑结构及数据显控总流程,描述了显示数据与控制文件中显示控制说明项的对应关系,最后给出了一种高效、灵活、易扩充的控制文件实现方法。     

基于图象的人体运动追踪系统研究

首先介绍了运动测量的几种主要方法,讨论了基于图象的运动追踪研究中要考虑的时间延迟问题及多摄像机的采集同步问题,最后介绍了一个能较好地完成大尺度空间人体无约束追踪的基于透视四点投影(P4P)问题的单摄像机运动追踪实验系统,包括摄像机标定、图象处理、特征提取、特征匹配、深度估计和姿态估计等等技术。     

含趋势项时间序列持久性变点监测

针对核加权方差比率统计量不是监测从非平稳向平稳变化持久性变点一致方法的问题,通过引进一个窗宽参数,提出了一种滑动核加权方差比率统计量来监测含趋势项时间序列从非平稳向平稳变化的持久性.在非平稳原假设下给出了监测统计量的极限分布和经验临界值表,在备择假设下证明了新方法的一致性.模拟结果表明新方法具有比原方法更高的势和更短的平均运行长度,最后通过分析人民币与美元汇率数据进一步说明了该方法的有效性.     

局域波法和高阶统计量在压缩机气阀状态监测中应用

为解决传统信号处理方法分析非平稳时变信号的不足,提出了一种适用于往复式压缩机气阀状态特征提取的新方法.首先使用局域波法将实测信号分解为多个基本模式分量,经过希尔伯特变换得到各分量的时频谱;然后计算归一化后幅值信号的高阶统计量,这些统计量很好地反映了气阀的劣化过程.通过对现场工作的聚乙烯二次压缩机组合阀振动信号的分析,验证了该方法在往复压缩机状态监测中的有效性和实用性.     

黄大铁路黄河特大桥顶推施工分析与监控技术

针对黄大铁路黄河特大桥连续钢桁梁多点同步顶推施工,利用倒拆法建模计算顶推施工全过程,找出主桁杆件在支点处的最大应力值以及导梁悬臂端变形规律和最大变形值,确定出全过程施工中的最不利工况为M2工况;设置变形监测点,监控导梁前段竖向位移变形,实测值基本与理论值吻合,施工线形可控;在M2工况中,将主桁和导梁自重荷载乘以1.35的放大系数,计算主梁在导梁悬臂140m,悬臂160m和导梁上墩20m后的主桁杆件的应力值,并在主桁上设置24个监测点监测杆件应力值,对比发现实测值均略小于理论值,施工过程中材料强度储备是安全可靠的。作为国内最大跨度的平行弦桁架桥顶推成功,对其他同类大跨度桥梁顶推施工具有较高的参考价值。     

Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR

In this paper, we first extract factors from a monthly dataset of 130 macroeconomic and financial variables. These extracted factors are then used to construct a factor‐augmented qualitative vector autoregressive (FA‐Qual VAR) model to forecast industrial production growth, inflation, the Federal funds rate, and the term spread based on a pseudo out‐of‐sample recursive forecasting exercise over an out‐of‐sample period of 1980:1 to 2014:12, using an in‐sample period of 1960:1 to 1979:12. Short‐, medium‐, and long‐run horizons of 1, 6, 12, and 24 months ahead are considered. The forecast from the FA‐Qual VAR is compared with that of a standard VAR model, a Qual VAR model, and a factor‐augmented VAR (FAVAR). In general, we observe that the FA‐Qual VAR tends to perform significantly better than the VAR, Qual VAR and FAVAR (barring some exceptions relative to the latter). In addition, we find that the Qual VARs are also well equipped in forecasting probability of recessions when compared to probit models.     

Predicting Recessions with Leading Indicators: Model Averaging and Selection over the Business Cycle

Four methods of model selection—equally weighted forecasts, Bayesian model‐averaged forecasts, and two models produced by the machine‐learning algorithm boosting—are applied to the problem of predicting business cycle turning points with a set of common macroeconomic variables. The methods address a fundamental problem faced by forecasters: the most useful model is simple but makes use of all relevant indicators. The results indicate that successful models of recession condition on different economic indicators at different forecast horizons. Predictors that describe real economic activity provide the clearest signal of recession at very short horizons. In contrast, signals from housing and financial markets produce the best forecasts at longer forecast horizons. A real‐time forecast experiment explores the predictability of the 2001 and 2007 recessions. Copyright © 2015 John Wiley & Sons, Ltd.