内插法在相关干涉仪测向体制中的应用

测向误差的减小一直以来都是无线电测向精度提高的一个难点,对于不同的测向体制所采用的减小测向误差的方法都不尽相同。本文主要介绍的是相关干涉仪测向体制的基本原理以及通过内插法的应用来减小测向误差的方法。     

相关条件下基于N-P准则的分布式检测理论研究

本文针对并行网络、二元局部判决的情况,研究了在相关条件下基于N-P准则的分布式检测融合算法,给出了在联合概率密度已知和未知两种情况下的最优融合规则的理论推导及相应的解决方案,并在实验仿真的基础上,得到了部分有益的结论。     

以一种新的距离度量作为反馈的相关跟踪方法

基于相关的模板匹配方法在图像跟踪中得到了广泛的应用,但是这种方法的主要缺点是对图像噪声非常敏感,而且由这种方法得出的相关曲面比较平坦。为了有效抑制噪声和局部遮挡对图像的影响,提出用鲁棒统计中的一个值代替相关值作为距离度量。它不是计算两幅图像的对应像素差值,而是计算两幅图像中差别不大的对应像素对的个数。实验证明这样得到的曲面相对　　收稿日期:2003 08 31;　修订日期:2003 10 28作者简介:张桂林(1944 ),男,天津人,教授,博士生导师,主要研究方向为自动识别、人体生物统计特征识别、图像处理算法与系统性能评估等。　　　　　　　要尖锐得多。当上述的距离度量应用于跟踪过程中时,模板的合理更新对跟踪非常重要。基于上述的距离度量方法,提出了一种新的模板更新策略。利用两幅图像中近似像素在整修匹配模板像素中所占的比例大小决定加权系数。这种加权策略可以自适应地根据图像序列的变化选择更新相关模板,同时在一定程度上减小模板漂移的危险。     

掺气减蚀保护作用的新概念

利用针式掺气流速仪测量原型和模型掺气浓度场、流速场，气泡尺寸及其概率分布的研究成果表明，原型水流韦伯数高，形成微小气泡的能力比模型强，气泡上浮慢，接近底部的小尺寸气泡概率及掺气浓度比模型大。初步研究认为：0.2mm或0.5mm以下的微小气泡在掺气减蚀中起着主要作用，可能只要很小掺气浓度即可达到掺气减蚀的效果。因此以小尺寸气泡的掺气浓度，作为判断掺气减蚀保护作用的指标将更为准确。     

火工品压药机装配误差的研究

针对军用雷管生产线中压药机结构,分别用极值法和概率法对压药机冲子和雷管的配合精度,进行了装配尺寸链的描述和计算,并对所得的结果进行了比较。     

大麻工艺纤维长度与细度的相关性初探

通过对大麻工艺纤维长度和直径投影宽度的相关性研究，认为大麻工艺纤维长度和细度之间存在“越长越粗，越短越细”的规律。     

Efficient Spreadsheet Algorithm for First-Order Reliability Method

A new spreadsheet-cell-object-oriented algorithm for the first-order reliability method is proposed and illustrated for cases with correlated nonnormals and explicit and implicit performance functions. The new approach differs from the writers earlier algorithm by obviating the need for computations of equivalent normal means and equivalent normal standard deviations. It obtains the solution faster and is more efficient, robust, and succinct. Other advantages include ease of initialization prior to constrained optimization, ease of randomization of initial values for checking robustness, and fewer required optimization constraints during spreadsheet-automated search for the design point. Two cases with implicit performance functions, namely an asymmetrically loaded beam on Winkler medium and a strut with complex supports are analyzed using the new approach and discussed. Comparisons are also made between the proposed approach and that based on Rosenblatt transformation.     

构造性神经网络在测井岩性识别中的应用

测井岩性识别是石油勘探中十分重要的基础工作,准确的岩性识别结果可以为勘探和开发提供可靠的依据。人工神经网络方法可对复杂的高维数据进行非线性映射,在模式识别领域得到越来越广泛的应用。针对传统的BP神经网络算法存在收敛速度慢、隐层数以及隐层节点数难以确定等缺点,研究了一种构造性神经网络学习算法---级联算法（Cascade Correlation Algorithm,简称CC算法）及其在石油工程中的应用。采用该算法对甘肃镇原-泾川地区进行岩性识别研究,通过与BP神经网络的识别结果进行比较,体现出构造性神经网络的优越性。     

Plastic Limit, Liquid Limit and Undrained Shear Strength of Soil—Reappraisal

The concept that plasticity index of soils can be defined as a range of water contents producing a 100-fold variation in undrained shear strength has been experimentally verified with the help of a large number of tests on soils of diverse nature. This has led to the redefinition of the plastic limit as the water content at which undrained shear strength is around 170 kN/m2. Undrained shear strength of a soil at the liquid limit can be considered to be around 1.7 kN/m2. Accordingly, both the liquid limit and the plastic limit have been determined in the present work by a single consistent method, i.e., the Swedish fall cone method. The undrained shear strength-water content relationship has been found to be log-linear for a wide range of water contents beginning from lower than the plastic limit to higher than the liquid limit. This resulted in the formulation of an expression for predicting undrained shear strength of a remolded soil at any water content based solely on its liquid limit and plastic limit.