跨断层形变监测研究进展

对比中外跨断层形变监测研究进展,认为中外跨断层形变监测在监测目的、监测区域控制范围大小、监测断裂活动年代要求、监测周期、监测地区等存在差别,而且中国跨断层形变监测具有细致周全的监测规范。中国开展跨断层形变监测,有利于最大限度地提高地震活动监控能力和监测水平。     

镇江地震台网理论监测能力评估

基于近震震级公式,对镇江地震台网理论监测能力进行评估,绘制地震监测能力图,以确定监测区不同地点发生地震时能被台网有效分析和定位的地震最小震级。镇江市句容县在该台网理论监测震级最小,为ML1.2—1.3;在镇江及相邻城市,发生M_L 1.8分析认为,以上地震均能被有效监测。     

辽宁省地震重点监视防御区典型村镇房屋抗震现状调查与分析

为了解辽宁省地震重点监视防御区典型村镇房屋抗震能力现状,通过现场调查的方式对辽阳、锦州和盘锦等地的村镇民居进行了随机抽样调查,并从场地选择、地基基础、建筑材料、构件的连接及抗震构造措施等方面对其抗震性能进行了分析。总体上看:房屋抗震能力不足的比例占85%左右,主要体现在抗震构造措施缺失及构件连接问题上。在此基础上对提高村镇房屋抗震性能提出了一些对策和建议,为辽宁省农村防震减灾工作提供参考。     

Application of the HY-1 satellite to sea ice monitoring and forecasting

The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002～2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the first time. The sea ice retrieval system of the HY-1A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.     

Bayesian probabilistic damage detection of a reinforced‐concrete bridge column

A Bayesian probabilistic approach for damage detection has been proposed for the continuous monitoring of civil structures (Sohn H, Law KH. Bayesian probabilistic approach for structure damage detection. Earthquake Engineering and Structural Dynamics 1997; 26 :1259–1281). This paper describes the application of the Bayesian approach to predict the location of plastic hinge deformation using the experimental data obtained from the vibration tests of a reinforced‐concrete bridge column. The column was statically pushed incrementally with lateral displacements until a plastic hinge is fully formed at the bottom portion of the column. Vibration tests were performed at different damage stages. The proposed damage detection method was able to locate the damaged region using a simplified analytical model and the modal parameters estimated from the vibration tests, although (1) only the first bending and first torsional modes were estimated from the experimental test data, (2) the locations where the accelerations were measured did not coincide with the degrees of freedom of the analytical model, and (3) there existed discrepancies between the undamaged test structure and the analytical model. The Bayesian framework was able to systematically update the damage probabilities when new test data became available. Better diagnosis was obtained by employing multiple data sets than just by using each test data set separately. Copyright © 2000 John Wiley & Sons, Ltd.     

东胜体育场钢结构施工临时支撑体系监测

东胜体育场是我国目前国内规模最大的开闭顶体育建筑,固定屋盖和巨拱使用大跨度钢桁架结构,采用分段拼装的方法施工,在施工期间屋盖和巨拱的1万吨重力荷载大部分由临时支撑体系承担,为保障支撑体系的安全,在钢结构施工期间,对临时支撑体系垂直度、侧向弯曲,位移、基础沉降进行动态监测。本文介绍了监测方法和监测结果,对类似工程有借鉴意义。     

自适应移动盒子的机载LiDAR点云去噪算法

针对现有LiDAR点云去噪算法难以实现自适应的问题,该文提出了基于空间盒子结构的自适应移动盒子去噪算法。基于经验模型建立盒子自适应准则,较好规避了现有算法的去噪阈值确定问题;采用聚类分析实现噪声点与有效点的精确标示。基于不同类型噪声的点云数据实验结果表明:与现有去噪算法相比,基于自适应移动盒子的去噪算法具有更好的适应性和去噪效果。     

典型风力条件及水力调度下太湖藻华高频时空动态监测

湖泊藻华问题已成为全球水生态环境领域面临的长期挑战,风力条件变化和引调水工程的水力调度能改变湖体水动力结构,对藻类的生长和聚集过程产生影响,进行该过程的精细化监测和机制分析对于湖泊藻华预报预警和应急处置具有重要意义。本研究基于Hiamwari-8/AHI卫星遥感高频监测数据,对比分析了归一化差异植被指数(NDVI)、增强植被指数(EVI)和浮游藻类指数(FAI) 3种不同指数对太湖藻华的反演效果,开展了典型风力条件下和水力调度下太湖藻华生消过程的持续监测分析。结果表明,FAI对藻华区域和非藻华区域的区分更加明显,其阈值提取的藻华面积与基于MODIS图像解译的藻华面积的相对误差最低,为-2.27%。当营养盐充足且水温持续保持在蓝藻大量生长增殖的阈值以上时,风力条件是导致太湖藻类迁移聚集的关键因子,风向主要影响藻类的水平迁移,使其进行方向性迁移并逐渐形成大面积藻华区域。风速主要影响藻类的垂向迁移并存在临界阈值,当风速低于约2.5 m/s的临界风速时,藻华面积随风速增加而增加;当风速高于临界风速时,藻华面积随风速增加而降低。水力调度对距离较近的贡湖湾区域具有显著影响,主要通过水动力扰动来影响...     

An improved segmentation approach for planar surfaces from unstructured 3D point clouds

The extraction of object features from massive unstructured point clouds with different local densities, especially in the presence of random noisy points, is not a trivial task even if that feature is a planar surface. Segmentation is the most important step in the feature extraction process. In practice, most segmentation approaches use geometrical information to segment the 3D point cloud. The features generally include the position of each point (X, Y and Z), locally estimated surface normals and residuals of best fitting surfaces; however, these features could be affected by noisy points and in consequence directly affect the segmentation results. Therefore, massive unstructured and noisy point clouds also lead to bad segmentation (over-segmentation, under-segmentation or no segmentation). While the RANSAC (random sample consensus) algorithm is effective in the presence of noise and outliers, it has two significant disadvantages, namely, its efficiency and the fact that the plane detected by RANSAC may not necessarily belong to the same object surface; that is, spurious surfaces may appear, especially in the case of parallel-gradual planar surfaces such as stairs. The innovative idea proposed in this paper is a modification for the RANSAC algorithm called Seq-NV-RANSAC. This algorithm checks the normal vector (NV) between the existing point clouds and the hypothesised RANSAC plane, which is created by three random points, under an intuitive threshold value. After extracting the first plane, this process is repeated sequentially (Seq) and automatically, until no planar surfaces can be extracted from the remaining points under the existing threshold value. This prevents the extraction of spurious surfaces, brings an improvement in quality to the computed attributes and increases the degree of automation of surface extraction. Thus the best fit is achieved for the real existing surfaces.     

精密单点定位在机载GPS中的应用

推导了精密单点定位PPP(Precise Point Positioning)的基本原理及其解算流程。为达到分米级甚至厘米级的PPP精度,给出了基于传统模型PPP技术,PPP数据必须处理的几个关键问题。最终,在Matlab程序设计语言软件平台下开发了APTags 1.0软件包,并通过机载GPS动态数据测试得出了如下结论:序列历元的事后动态定位精确度在B,L,H方向优于25 cm(RMS);85%定位结果的精度优于15 cm的动态定位结果。APTags软件包获取的动态精密单点定位结果与传统差分定位结果基本吻合。