盾构机轴线方位角解算原理研究     

薄志义  王坡  张楠 《北京测绘》2006,(3):18-21

以德国VMT公司的TMB制导系统SLS-T为例,主要解析了盾构机轴线方位角测量原理,并完整地推导了盾构机姿态参数公式。由于国外导向系统的核心原理不公开,因此本文的研究成果,为隧道施工工程技术人员深入理解激光导向系统原理以及开发国产的自动导向系统提供了理论基础。  相似文献   

Upgrading of calcareous phosphate ores by flotation: Effect of ore characteristics   总被引：1，自引：0，他引：1  

A.-Z.M. Abouzeid  A.T. Negm  D.A. Elgillani 《International Journal of Mineral Processing》2009,90(1-4):81-89

Sedimentary phosphates contain-besides the phosphate minerals-, various associated gangue minerals such as: clays, silica, calcareous minerals (mainly calcite and dolomite), carbonaceous matter, iron oxides and/or pyrite. The common practiced flow-sheets for concentrating these types of phosphate ores consist of a combination of various mineral processing units such as: crushing and screening, attrition, washing, magnetic separation, and/or flotation. However, none of these combinations was successfully efficient to upgrade the calcareous ores because of the close similarity of the physical properties (density, particle size, particle shape, etc.) as well as the surface physico-chemical properties of the carbonate and phosphate minerals. For the last five decades extensive efforts have been spent to adopt flotation for separating carbonates from phosphate ores. These efforts include thermodynamic analysis, modification of the technique, controlling the pulp environment, and finding new reagents that can specifically differentiate between carbonates and phosphates.This paper reviews some of the published work on the separation of carbonates from phosphate ores by flotation and presents the flotation results of phosphate ore samples different in their physical properties and mineralogical composition. The results obtained reflect the effect of ore nature on the flotation performance and the reagents consumption.  相似文献   

Investigation on foaming properties of some organics for oily bubble bitumen flotation   总被引：1，自引：0，他引：1  

H.M. Tarkan  D.K. Bayliss  J.A. Finch   《International Journal of Mineral Processing》2009,90(1-4):90-96

Studies have shown that using organic coated bubbles (“oily” bubbles) could increase bitumen recovery rate in flotation. One way to coat bubbles is that used in the air-assisted solvent extraction process where solvent foam is formed and injected through a capillary to release solvent coated bubbles in a controlled manner into the aqueous system. To investigate adapting this approach, the foaming properties of some organics (Hexane, Heptane, Hexadecane, Petroleum Ether, Toluene, Benzene and Kerosene and their binary mixtures) of potential interest in oily bubble bitumen flotation were investigated. Silicone oil was found to be a good foaming agent in some cases. Bubble stability and film thickness experiments were carried out to help select candidate organics. Surface tension and dynamic viscosity measurements were conducted to examine the mechanism of foaming. Attachment studies showed that droplets of the selected organics readily attached to a bitumen surface compared to air bubbles. From a combination of criteria, 25:75 Hexadecane/Heptane appears to be a promising candidate.  相似文献   

Rejection of arsenic minerals in sulfide flotation — A literature review     

X. Ma  W.J. Bruckard 《International Journal of Mineral Processing》2009

Arsenic is one of the most dangerous inorganic pollutants and thus a penalty element in many base metal concentrates. Arsenic removal in sulphide flotation has been studied extensively with various approaches, including pre-oxidation of flotation pulp, E_h control during flotation and the use of selective depressants/collectors. Pre-oxidation of flotation pulp using oxidizing agents or aeration conditioning represents a simple approach in arsenic removal and was found effective in many cases. Selective flotation of arsenic minerals through E_h control has made significant advances in recent years with promising results achieved. In addition, various depressants and collectors have also been studied in arsenic removal. In this communication, the various approaches used in selective flotation of arsenic minerals are reviewed with emphasis on the development in recent years.  相似文献   

高光谱遥感影像分类研究进展   总被引：4，自引：0，他引：4  

杜培军  夏俊士  薛朝辉  谭琨  苏红军  鲍蕊 《遥感学报》2016,20(2):236-256

随着模式识别、机器学习、遥感技术等相关学科领域的发展,高光谱遥感影像分类研究取得快速进展。本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展,在总结分类策略的基础上,重点从以核方法为代表的新型分类器设计、特征挖掘、空间-光谱分类、基于主动学习和半监督学习的分类、基于稀疏表达的分类、多分类器集成六个方面对高光谱影像像素级分类最新研究进行了综述。针对今后的研究方向,指出高光谱遥感影像分类一方面要适应大数据、智能化高光谱对地观测的发展前沿,继续引入机器学习领域的新理论、新方法,综合利用多源遥感数据、多维特征空间互补的优势,提高分类精度、分类器泛化能力和自动化程度;另一方面要关注高光谱遥感应用的需求,突出高光谱遥感记录精细光谱特征的优势,针对应用需求发展有效的分类方法。  相似文献   

基于机器学习的地震动特征提取与模拟以2021年云南漾濞6.4级地震为例          下载免费PDF全文

靳超越  胡进军  胡磊  王中伟 《世界地震工程》2021,(4):073-80

随着地震动数据数量的增长和质量的提高,将基于数据驱动的机器学习方法应用到地震动模拟中有重要意义。以2021年5月21日云南漾濞M_S6.4地震为例,利用主成分析方法从前震及余震地震动记录中提取特征母波时程,将地震动三要素作为模拟误差约束,在求解母波的线性组合系数时使用多目标优化算法寻优,最终找到帕累托最优解作为模拟目标台站记录时的组合系数,得到模拟地震动时程。结果表明:主成分析法在对实际地震动记录进行特征提取后,得到的特征母波时程可以在一定程度上保留原始数据的主要信息;考虑幅值、频谱和持时这三要素的角度去控制模拟误差,可以使得模拟的地震动时程更加接近真实记录。提出的基于特征提取的地震动模拟方法可以为基于小震数据合成大震地震动提供参考。  相似文献   

基于灰色关联度模型的区域滑坡敏感性评价   总被引：2，自引：0，他引：2       下载免费PDF全文

黄发明  汪洋  董志良  吴礼舟  郭子正  张泰丽 《地球科学》2019,44(2):664-676

数理统计和机器学习模型如支持向量机(support vector machine,SVM)等,在区域滑坡敏感性评价中得到广泛的应用.但这些模型的建模过程往往较复杂,如在对机器学习进行训练和测试时难以选取合理的非滑坡栅格单元,而且有较多的模型参数需要确定.为提高滑坡敏感性评价建模的效率和精度,提出基于灰色关联度的敏感性评价模型.灰色关联度模型能有效计算各比较样本与参考样本之间的定量的关联度,具有建模过程简洁和评价精度高的优点,该模型目前在区域滑坡敏感性评价中的应用还没有引起研究人员的足够关注且有待进一步拓展.拟将灰色关联度模型用于浙江省飞云江流域南田—雅梅图幅(南田地区)的滑坡敏感性评价,并将得到的评价结果与SVM模型的敏感性评价结果作对比分析.结果显示,灰色关联度模型在高和极高敏感区的滑坡预测精度优于SVM模型,而在中等敏感区的滑坡预测精度略低于SVM模型;整体而言,灰色关联度模型对整个南田地区滑坡敏感性分布的预测精度略高于SVM模型.对两个模型建模过程的对比结果显示,灰色关联度模型建模较简单,具有比SVM模型更高的建模效率,为滑坡敏感性评价提供了一种新思路.  相似文献   

基于粒子群算法优化小波支持向量机的岩土力学参数反演     

阮永芬  高春钦  刘克文  贾荣谷  丁海涛 《岩土力学》2019,(9):3662-3669

常用的确定岩土力学参数的方法有原位测试和室内试验两种,但都存在一定的局限性,参数选择的合理与否,对设计计算及数值模拟分析结果的有效性影响很大。支持向量机法在理论基础和求解算法方面都具有明显优势,为确保岩土力学参数取值的合理性,采用支持向量机法对岩土力学参数进行反演。先通过小波分析理论构造出支持向量机的核函数,再用粒子群算法(PSO)分别优化Morlet小波、Mexico小波和RBF函数的支持向量机模型参数,通过小波支持向量机模型建立反演参数与沉降值间的非线性映射关系。根据正交试验和均匀试验对需反演的岩土力学参数进行设计,结合有限元软件进行计算分析,得到学习样本和测试样本。分别采用Morlet小波、Mexico小波和RBF函数得出的预测结果和原始数据进行对比分析,发现采用Morlet小波核函数预测效果更佳。使用Morlet小波核函数预测的参数输入到Midas模型中计算建筑物最终沉降量,比较计算值与实际监测值,其相对误差不超过8.1%。研究结果表明,该方法在岩土工程参数的反演中具有良好的应用价值,对今后岩土力学参数的确定及校核提供了一种新方法。  相似文献   

Application of PSO-LIBSVM in Recognition of Potassium Salt Deposits     

Fuqiang Yang  Kegui Chen  Changbing Huang  Yuanyuan Chen  Jin Li  Xiaolin Ma 《地球科学进展》2019,34(7):757-764

The shortage of potassium salt seriously restricts the development of China's agriculture. Increasing the exploration and development of potash will help improve the self-sufficiency of potassium in China. With rich potassium salt resources, Sichuan basin is one of the most important research areas for potash exploration and development in China. Polyhalite is an important solid potassium salt mineral in Sichuan basin, often intercalated in rock minerals such as anhydrite, rock salt and dolomite. Aiming at the problem that conventional log interpretation methods are difficult to accurately identify polyhalites, this paper proposed a new Support Vector Machine (SVM) recognition method based on Particle Swarm Optimization (PSO) to classify polyhalites in Sichuan basin. Based on particle swarm optimization and support vector machine theory, combined with logging interpretation theory, the effective data sensitive to polyhalite logging response were selected as input samples to generate training sets and test sets randomly. The Radial Basis Function (RBF) parameters were optimized by particle swarm optimization, and the classification and prediction model of polyhalite was established. Compared with mud logging results, the recognition accuracy of SVM model based on particle swarm optimization reached 97.5758%, which is obviously better than that of SVM model optimized by cross validation method in recognition accuracy and speed. The results show that the model has broad application prospects in potash exploration in Sichuan basin.  相似文献   

勘查地球化学数据挖掘与弱异常识别     

左仁广 《地学前缘》2019,26(4):67-75

我国积累的大量高质量、多元素、多尺度的地球化学数据,为矿产勘查与环境评价提供了有效的数据支撑。如何对这些数据进行二次开发和再利用,提取有价值的地球化学异常信息并带动找矿突破,是缓解当前矿产资源短缺的重要途径之一。在覆盖区和深部的找矿实践中,由于矿体埋深和覆盖层的影响,往往在表生介质中形成弱小的地球化学异常,识别和评价弱小地球化学异常是当前勘查地球化学数据处理的重要方向之一。本文围绕地球化学异常信息的提取和评价,主要从以下几个方面讨论了相关的国内外研究进展和发展趋势:勘查地球化学数据处理与异常识别方法和模型,勘查地球化学数据闭合效应的影响及其解决方案,基于大数据和机器学习的勘查地球化学数据处理以及弱小地球化学异常的识别和评价。研究发现,在地质环境的约束下,基于大数据思维和机器学习相结合的方法,注重地球化学空间分布模式与已发现矿床的相关关系,同时使用所有地球化学变量能有效刻画具有非线性特征的地球化学空间分布模式,可识别出传统方法无法识别的异常,为开展地球化学空间模式识别与异常提取提供了新的途径。  相似文献