一类载人潜水器的导航技术研究

介绍了一类载人潜水器导航系统的组成,接着阐述了基于工业以太网的信息采集模块.由于载人潜水器动力学模型存在未建模扰动以及各种传感器存在不同程度的误差,需要采用卡尔曼滤波器(KF)等方法进行数据滤波,最后将滤波后的数据用于该类载人潜水器的导航研究.半物理仿真平台结果表明,载人潜水器的导航精度得到了大幅度提高.

WAGO750模块与PC机之间的通讯

介绍了一种用于WAGO750-842以太网节点及系列模块与PC机之间的一种通用而又简便的通讯方法,该方法能够使PC机与WAGO750系列模块方便地进行数据交换,从而达到计算机对控制对象进行信息采集和控制输出的目的。该方法已在载人潜水器控制系统中得到成功应用,效果良好。

景物的三维信息获取及其运动分析

采用模糊熵函数对图象象素分类作出整体最优分类评价,实现了区域分割.利用矩及其函数做为各区域的特征表达,构成以区域为基元的符号特征集并描述图象内容。根据立体图象对间的几何关系,解出各区域(基元)的相对三维坐标。与象索匹配相比较,它可以获得较高精度的三维信息和可描述的景物信息.通过获取不同时空的各区域(基元)三维信息,确定了它们的空间运动状态。联系这些状态,构造出景物中物体间的空间关系和近似模型,实现了对景物的3-D识别和描述。

基于Zernike矩边缘检测的焊缝信息获取

针对目前焊缝坐标提取方法存在精度较低,难于实现视觉引导的机器人激光焊接高速度、高精度的要求,提出一种基于Zernike正交矩的曲线焊缝位置坐标信息获取算法,该算法首先采用Zernike边缘检测算法识别焊缝边缘,然后提取出焊缝的中心线,最后计算出该中心线的亚像素坐标。通过试验验证了该算法的可行性。

基于视觉测量的机器人激光焊接信息获取及路径规划

随着计算机视觉与机器人智能控制学科的飞速发展，在汽车工业中，结合视觉测量和机器人控制技术，采用激光拼焊方式加工汽车车身零部件显示出愈来愈重要的作用。在国外汽车板材激光拼焊技术已获得广泛应用，而在国内还只是处于研发和试生产阶段。应用工业机器人进行激光拼焊，不仅能充分发挥工业机器人灵活性、智能性等特点，而且还能代替大型激光拼焊装备进行生产，降低成本，提高效益。本课题以激光拼焊为背景，以搭建的工业机器人激光拼焊试验系统为研究平台，对基于视觉的激光焊接机器人焊缝位置信息获取及路径规划技术进行了研究。 在众多的信息获取方法中，立体视觉是一种有效的三维信息获取技术。一个完整的立体视觉过程包括：图像获取、特征提取、摄像机标定、立体匹配、深度信息计算和插值六个部分。单个摄像机获取的图像是二维的，图像的深度信息丢失。采用两个相同的摄像机在不同位置对被测物件取像，通过立体视觉匹配能计算出图像的深度信息。为避免立体匹配的困难，采用结构光代替其中一个摄像机是行之有效的方法。基于视觉的激光焊接机器人焊缝位置信息获取是立体视觉技术在激光焊接机器人焊接作业中的典型应用。对由CCD摄像机拍摄到工件图像进行算法处理提取出焊缝特征信息，是基于视觉的激光焊接机器人系统中关键技术之一。 图像处理的精度直接影响到整个视觉测量系统的精度，获取的焊缝位置信息的准确性直接决定着焊接任务的成败。焊缝在图像上表现为两条边缘，在成像条件较好的情况下，可以采用边缘特征提取的方法来获取工件焊缝的位置信息。亚像素边缘检测是近年来较为流行的边缘检测算法，检测的边缘精度可以达到亚像素级别。基于Zernike矩的亚像素边缘检测算法具有很好的抗噪性，适用于激光焊缝信息的提取，但检测出的边缘较粗，本文针对Zernike矩亚像素边缘检测存在的不足进行了算法改进，推导出7×7模板系数，并提出了新的边缘判断依据。试验验证了改进算法的有效性。改进的算法能获取焊缝位置精确信息。 阐述了Tsai两步法和Zhang的基于平面靶标标定的原理和标定过程。提出双线结构光视觉测量系统，建立了用于跟踪曲线焊缝的双线结构光视觉系统的数学模型，并给出标定方法。该方法首先采用Zhang的标定方法对摄像机进行标定，然后基于交比不变性原理，对结构光平面进行拟合。双线结构光视觉系统在跟踪曲线焊缝时，在一帧图像中可以同时检测出焊缝转角偏差和位置偏差，应用在机器人激光焊接焊缝跟踪上可获得比单线结构光更加丰富的信息。 激光焊接机器人焊枪的位姿直接影响着焊接质量的好坏。本文研究了机器人末端执行器位姿表达方法，建立了焊枪位姿和焊缝坐标系的数学模型。在激光焊接机器人焊接之前需要对焊缝编程，阐述了焊接机器人编程原理。针对在圆弧焊缝曲率变化较大的地方采用视觉测量方法存在较大的测量误差，提出偏转角的概念，对偏转角提前进行补偿，能明显提高焊接质量。 设计了测量焊接机器人轨迹误差的试验，对激光焊接机器人在高速焊接或焊接曲率较大的圆弧时轨迹误差进行了测量和分析。归纳了焊接机器人轨迹误差的来源及其产生的原因。给出了一种补偿机器人轨迹误差的方法。该方法的基本思想是先由结构光视觉系统测量出焊接机器人的重复轨迹误差，然后由视觉伺服系统补偿。实验证明，该方法应用在长焊缝和曲线焊缝焊接时，能有效补偿焊接机器人的轨迹误差。

非自喷层测试及评价解释技术研究与应用

Now low porosity and low permeability reservoir is one of the main targets of exploration for the onshore oilfields of China. Most of the reservoirs are none flowing because of bad formation percolation condition, poor gas oil ratio , low formation pressure coefficient and other factors. In the recent years, a number of domestic oilfields have carried out some research work and achieved some success on oil testing and production technology in such formation. But by now, there is still no systematic and mature technology, particularly testing technology in none flowing formation is still needed further study. Based on study the key problem of well testing and interpretation technology in none flowing formation, solve the important problems in well testing technology, continuously improve and innovate geological information acquisition technology for none flowing reservoir, accurately acquire boundary information and evaluate reservoir flow characteristics. Its wide application remarkable result has shown. The main results and cognitions obtained from research are as follows: 1. This new technology research results help solve the occurrent problems in well testing process for none flowing formations, such as small investigation radius, poor representative of interpretation results from the poor data, low level application of interpretation results. This new technology helps create favorable conditions for early precise reservoir evaluation and reduction of the risk of exploration. 2. The technological difficulties for none flowing well testing are successfully solved by using none flowing formation combined mechanical tool string .This method has been proved by its applications to be able to improve the efficiency of the testing and the quantity of the acquired test data ,and so as to enhance the application of the interpretation results of the test in development of oil fields. 3. The application of the rotary formation tester, selective test valve, well testing string and their allier tools help to resolve problems such as the operation of opening and shutting-in the well under different well conditions, to broaden the scope of well test technology for none flowing formations. 4. Refined Testing Technique for production Wells has greatly shortened the testing dwration and improved the efficiency and accuracy of operation, enriched test results, and at the same time created conditions for conducting multi-well interference well testing.

滑坡泥石流信息遥感获取与空间预测

On the issue of geological hazard evaluation（GHE）, taking remote sensing and GIS systems as experimental environment, assisting with some programming development, this thesis combines multi-knowledges of geo-hazard mechanism, statistic learning, remote sensing (RS), high-spectral recognition, spatial analysis, digital photogrammetry as well as mineralogy, and selects geo-hazard samples from Hong Kong and Three Parallel River region as experimental data, to study two kinds of core questions of GHE, geo-hazard information acquiring and evaluation model. In the aspect of landslide information acquiring by RS, three detailed topics are presented, image enhance for visual interpretation, automatic recognition of landslide as well as quantitative mineral mapping. As to the evaluation model, the latest and powerful data mining method, support vector machine (SVM), is introduced to GHE field, and a serious of comparing experiments are carried out to verify its feasibility and efficiency. Furthermore, this paper proposes a method to forecast the distribution of landslides if rainfall in future is known baseing on historical rainfall and corresponding landslide susceptibility map. The details are as following: (a) Remote sensing image enhancing methods for geo-hazard visual interpretation. The effect of visual interpretation is determined by RS data and image enhancing method, for which the most effective and regular technique is image merge between high-spatial image and multi-spectral image, but there are few researches concerning the merging methods of geo-hazard recognition. By the comparing experimental of six mainstream merging methods and combination of different remote sensing data source, this thesis presents merits of each method ,and qualitatively analyzes the effect of spatial resolution, spectral resolution and time phase on merging image. (b) Automatic recognition of shallow landslide by RS image. The inventory of landslide is the base of landslide forecast and landslide study. If persistent collecting of landslide events, updating the geo-hazard inventory in time, and promoting prediction model incessantly, the accuracy of forecast would be boosted step by step. RS technique is a feasible method to obtain landslide information, which is determined by the feature of geo-hazard distribution. An automatic hierarchical approach is proposed to identify shallow landslides in vegetable region by the combination of multi-spectral RS imagery and DEM derivatives, and the experiment is also drilled to inspect its efficiency. (c) Hazard-causing factors obtaining. Accurate environmental factors are the key to analyze and predict the risk of regional geological hazard. As to predict huge debris flow, the main challenge is still to determine the startup material and its volume in debris flow source region. Exerting the merits of various RS technique, this thesis presents the methods to obtain two important hazard-causing factors, DEM and alteration mineral, and through spatial analysis, finds the relationship between hydrothermal clay alteration minerals and geo-hazards in the arid-hot valleys of Three Parallel Rivers region. (d) Applying support vector machine (SVM) to landslide susceptibility mapping. Introduce the latest and powerful statistical learning theory, SVM, to RGHE. SVM that proved an efficient statistic learning method can deal with two-class and one-class samples, with feature avoiding produce ‘pseudo’ samples. 55 years historical samples in a natural terrain of Hong Kong are used to assess this method, whose susceptibility maps obtained by one-class SVM and two-class SVM are compared to that obtained by logistic regression method. It can conclude that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, only requires failed cases, has an advantage over the other two methods as only "failed" case information is usually available in landslide susceptibility mapping. (e) Predicting the distribution of rainfall-induced landslides by time-series analysis. Rainfall is the most dominating factor to bring in landslides. More than 90% losing and casualty by landslides is introduced by rainfall, so predicting landslide sites under certain rainfall is an important geological evaluating issue. With full considering the contribution of stable factors (landslide susceptibility map) and dynamic factors (rainfall), the time-series linear regression analysis between rainfall and landslide risk mapis presented, and experiments based on true samples prove that this method is perfect in natural region of Hong Kong. The following 4 practicable or original findings are obtained: 1) The RS ways to enhance geo-hazards image, automatic recognize shallow landslides, obtain DEM and mineral are studied, and the detailed operating steps are given through examples. The conclusion is practical strongly. 2) The explorative researching about relationship between geo-hazards and alteration mineral in arid-hot valley of Jinshajiang river is presented. Based on standard USGS mineral spectrum, the distribution of hydrothermal alteration mineral is mapped by SAM method. Through statistic analysis between debris flows and hazard-causing factors, the strong correlation between debris flows and clay minerals is found and validated. 3) Applying SVM theory (especially one-class SVM theory) to the landslide susceptibility mapping and system evaluation for its performance is also carried out, which proves that advantages of SVM in this field. 4) Establishing time-serial prediction method for rainfall induced landslide distribution. In a natural study area, the distribution of landslides induced by a storm is predicted successfully under a real maximum 24h rainfall based on the regression between 4 historical storms and corresponding landslides.

Multi-sensors data acquisition and information fusion for manned submersible vehicle

本文介绍了一种用于载人潜水器的导航传感器的数据采集及信息融合技术。航行控制计算机通过基于工业以太网的数据通信系统对各传感器进行数据采集,采用卡尔曼滤波器完成对各传感器数据信息的融合,以便提高数据的精度和控制系统的性能,并将结果送给监控计算机,用于载人潜水器的姿态显示。