变压器油中溶解气体在线监测对变压器绝缘状态分析具有积极的指导作用，在线监测用气体传感器是实施该技术 的关键。本文针对半导体气体传感器的交叉敏感特性，提出了将气体传感器阵列与人工神经网络技术相结合，形成一种智能传感器，用于单一气体的定性识别和定量检测；利用六个半导体气体传感器组成传感器阵列，采用BP神经网络进行模式识别。通过大量的试验证明了本文提出的智能传感器可有效提高H2、CO、CH4、C2H4、C2H2、C2H6六种气体的分辨率和检测灵敏度。

本文提出了一种在快速暂态过电压作用下，基于准静态电磁场，以单匝中并联导线为单元支路和以两段线匝为单元支路相结合的集中参数混合线圈模型。对相关的参数计算进行了分析，并对以两段线饼为单元支路的线圈模型进行截波冲击下的仿真分析。

[1] More than a dozen of wind speed (U) algorithms have been proposed during the past 2 decades, as a result of a continuing effort to improve altimeter wind measurement. The progress in terms of accuracy, however, is seen to be rather slow. The reported root mean square (RMS) error of prevailing algorithms varies mostly between 1.6 and 2.0m/s for the dominant wind regime. As far as the TOPEX altimeter is concerned, three measured quantities, namely, the radar cross sections from Ku and C band (sKu and sC), as well as the significant wave height (Hs), have been used in previous algorithm developments, resulting in a variety of single-, dual-, and three-parameter model functions. On the basis of the finding of a banded dependency of the U-sKu relationship on sC a new pproach for retrieving altimeter wind speed, termed linear composite method (LCM), is proposed in this study. The LCM model function appears as a set of sC-dependent linear relations between U and sKu. A unique advantage of this approach is that it allows the algorithm to be tuned or expanded for a given range of wind speed without affecting the rest. Over 1.7 million coincident TOPEX/NASA scatterometer (NSCAT) and TOPEX/QuikSCAT data covering a period of 2.5 years are used to adjust the model. Validation against extensive buoy measurements indicates that the LCM algorithm is almost unbiased and has an overall RMS error of 1.56m/s, which is 12% lower compared to the algorithm in operational use [Witter and Chelton, 1991]. In addition, a small (2.5-6%, depending on the reference data set) but significant improvement is found for the LCM when compared to the most recent dual-parameter algorithm [Gourrion et al., 2002].

A detailed analysis on the effect of temporal allaying associated with TOPEX/Poseidon, Geosat, and ERS altimeters has been caried out. In the time domain, aliasing occurs when the original period of an oceanographic signal, To, is less than twice the satellite repeat orbit period, Ts. The most striking feature of temporal aliasing is that the alias period, To, appears as a quasi periodic &llke function with respect to Ts, and a non-periodic &-like function with respect to To. Histograms of Ta versus To suggest that signals wltb original periods between 0 and 2Ts are aliased onto periods ranging from 2Ts to with a rapidly decreasing probabilit3z The potential consequences of temporal aliasing in satellite altimetry are discussed in the context of orbit design and sampling strategy for geophysical applications.