利用地物杂波进行天气雷达强度标定

地物杂波的回波强度相对稳定 ,对成都和新疆地区的地物杂波强度的统计表明 ,地物杂波的雷达反射因子方差分别小于 3db和 1.5db ,因此 ,地物回波可作为一个标准目标 ,用来对天气雷达进行强度的标定。本文给出了这种强度标定的流程图、标定方法和标定结果。使用这种标定方法将大大改善天气雷达的维护和使用质量。     

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LCR重力仪与CG-5重力仪的长基线混合标定

2010-01-18—26日,在武汉、郑州、北京、沈阳4个高精度绝对重力点长基线上对8台LCR重力仪和4台CG 5重力仪进行了混合标定,标定结果表明：5台重力仪（其中4台为CG 5重力仪）显示出二次项的存在,但精度偏低。对于存在二次项的5台重力仪,一次项参数的单独标定结果均好于联合标定,其他重力仪的标定结果则基本保持不变。     

基于RCNN的无人机巡检图像电力小部件识别研究

随着无人机（UAV)在电力巡线作业中的应用推广,对无人机巡检图像的信息挖掘或目标识别需求也越来越强烈。传统的电力部件识别流程常使用经典的机器学习算法,如支持向量机（SVM）、随机森林或adaboost,结合梯度、颜色或纹理等浅层特征来对电力部件进行识别,难以充分利用无人机巡检图像的信息,并且难以达到较高的准确率。卷积神经网络（CNN）在目标识别中表现优异,在很多目标识别场景之中成为首选算法。基于区域的卷积神经网络（RCNN）通过使用CNN从图像中提取可能含有目标的区域来检测并识别目标,但是计算复杂,难以满足识别海量电力巡检图片的需求。Fast R-CNN和Faster R-CNN利用CNN网络提取图像特征,后接一个区域提议层,优化了提取可能含有目标区域的方式并改进识别目标的分类器,使目标的检测和识别几乎实时。本文详细描述了Faster R-CNN算法流程,并在无人机电力线巡检图像部件检测中使用,然后分别对DPM、SPPnet和Faster R-CNN识别方法进行了对比分析,利用实际采集的电力小部件巡检数据构建的数据集对3种方法进行测试验证,并讨论了不同参数对识别结果的影响。实验结果表明,基于深度学习的识别方法实现电力小部件的识别是可行的,而且利用Faster R-CNN进行多种类别的电力小部件识别定位可以达到每张近80 ms的识别速度和92.7%的准确率。     

Electromagnetic fields from a horizontal electrical dipole buried in ocean

Marine controlled source electromagnetic signal could be used in mineral resource exploration,reservoir appraisal and communicative technique in ocean. It’s necessary to study the electromagnetic generated by MCSEM. The propagation of the electromagnetic fields from a controlled source in the marine environment was studied with virtual interface method combined with discrete complex image method. Transmitter of finite length current source is approximated by dipole (HED) . A three-layered model is accepted,with sea water as intermediate conductive layer under air and a relatively high resistive seabed as basement,possibly containing a hydrogen layer of higher resistivity. The electromagnetic fields in whole space thus computed show that: (1) the spatial distribution of field component depends on its type; (2) inline Ex component is more sensitive to reservoir layer than that in broadside; (3) The airwave affects marine electromagnetic (MEM) exploration when sea water is relatively shallow; in the case of deep water MEM exploration,the airwave influence could be neglected; and (4) an appropriate frequency should be selected in order to balance the signal strength and electromagnetic induction effect.     

高密度电法勘探在岩溶地区地下水勘查中的应用

介绍了贵州省金沙县沙土镇大路村应用高密度电阻率法与激发极化法测深寻找地下水的应用及其钻探验证情况,说明应用高密度电阻率法确定含水构造的位置、形态,以及应用激电参数判别地下水的方法是可行的。     

地幔载流子热传导机制初步研究

本文采用Fermi量子统计方法,对地幔电导率和载流子热传导机制问题进行了理论上的探讨。讨论结果表明,在过渡带和下地幔中,以往被忽视的载流子热导将成为热传递的主要机制.此外,本文还指出在高温高压下活化能A对地幔电导率变化速率有重要影响。     

Application of high-density resistivity method for assessing construction safety of Shimodong tunnel in Helong City of Jilin Province

Some unfavorable geological conditions can affect the construction of tunnels.In order to evaluate the damage degree of tunnel construction and determine the surrounding rock grade and stability of the tunnel,the authors used high-density resistivity method to detect the surrounding rocks of Shimodong tunnel in Xicheng Town of Helong City.The underground resistivity structures of the entrance,exit and middle parts of the tunnel are obtained.Through analysis,it is found that there are no bedrock faults near the tunnel,although some joints and fissures are developed in some locations,which are characterized by low-resistivity anomalies.The tunnel structures are stable overall,favorable for safe and efficient construction.The study also proves the good application effect of the high-density resistivity method in tunnel safety detection.     

沿主光轴影像的单像空间后方交会方法研究

提出了一种沿主光轴方向影像的单像空间后方交会方法,实现了相机检校和空间后方交会的同时进行。实验证明,该方法达到了比较理想的精度。