On a near-optimal control approach for a wave energy converter in irregular waves

Real-time smooth reactive control and optimal damping of wave energy converters in irregular waves is difficult in part because the radiation impulse response function is real and causal, which constrains the frequency-dependent added mass and radiation damping according to the Kramers–Kronig relations. Optimal control for maximum energy conversion requires independent synthesis of the impulse response functions corresponding to these two quantities. Since both are non-causal (one being odd and other even), full cancellation of reactive forces and matching of radiation damping requires knowledge or estimation of device velocity into the future. To address this difficulty and the non-causality of the exciting force impulse response function, this paper investigates the use of propagating-wave surface elevation up-wave of the device to synthesize the necessary forces. Long-crested waves are assumed, and the approach is based on the formulations of Naito and Nakamura [2] and Falnes [22]. A predominantly heaving submerged device comprised of three vertically stacked discs driving a linear power take-off is studied. The overall formulation leads to smooth control that is near-optimal, given the approximations involved in the time-shifting of the non-causal impulse response functions and the consequent up-wave distances at which wave surface elevation is required. Absorbed power performance with the near-optimal approach is compared with two other cases, (i) when single-frequency tuning is used based on non-real time adjustment of the reactive and resistive loads to maximize conversion at the spectral peak frequency, and (ii) when no control is applied with damping set to a constant value. Simulation results for wave spectra over a range of energy periods and significant wave heights are compared for the three situations studied. While practical implementation presents engineering challenges, in terms of time-averaged absorbed power, unconstrained near-optimal control is found to perform significantly better than single-frequency tuning in the spectra with longer energy periods (>10 s for the present device), and somewhat better in the spectra with shorter energy periods (here ≤10 s).     

直驱式波浪能转换系统的研究和性能优化

A direct-drive wave energy conversion system based on a three-phase permanent magnet tubular linear generator （PMTLG） and a heaving buoy is proposed to convert wave energy into electrical energy. Sufficient experimental methods are adopted to compare the computer simulations, the validity of which is verified by the experiment results from a wave tank laboratory. In the experiment, the motion curves of heaving buoy are with small fluctuations, mainly caused by the PMTLG＇s detent force. For the reduction of these small fluctuations and a maximum operational efficiency of the direct-drive wave energy conversion system, the PMTLG＇s detent force minimization technique and the heaving buoy optimization will be discussed. It is discovered that the operational efficiency of the direct-drive wave energy conversion system increases dramatically after optimization. The experiment and optimization results will provide useful reference for the future research on ocean wave energy conversion system.     

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.     

Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping

Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas.     

一种解码接收机原始二进制数据的方法

本文对华迅G PS/BD双模接收机输出的原始二进制数据的格式进行了深入讨论,利用M atlab对其输出的二进制数据的解码并提取出观测值、星历等,该方法可以简捷快速的解码出所需要的观测信息。     

数据字典在地质矿产术语分类代码修编平台中的应用

基于B/S模式的《地质矿产术语分类代码》（GB 9649-1988）修编平台是提高该标准修编工作效率的一种必然手段,而数据字典在该平台中的穿插使用保证了修编工作的合理与安全.通过论述数据字典技术在实现修编平台的修编权限控制、修编版本管理功能中的具体应用,体现了数据字典技术在数据处理方面的独特优势.数据字典技术在该平台中的应用,不仅对修编人员的修编权限进行了灵活的约束,而且修编过程中产生的不同版本也得到了有效的管理.     

物探软件MAGS2.0在峨腊厂高精度磁测中的应用

划分出3个磁异常场区,Ⅲ区规模较大.出露中元古界昆阳群大龙口组,是勘查区内铁矿床的赋矿层位,受断裂构造和岩体控制.     

大数据环境下地理信息产业发展的几点思考

大数据背景下地理信息产业的发展有了新的驱动力,通过思考这种驱动力对产业发展可能产生的影响,分析指出了大数据在地理信息产业中的中心地位和重要价值,综述了大数据给地理信息产业的涵盖范围、关键技术和服务模式所带来的重大变革,探讨了大数据技术对于GIS传统技术优化升级的几个着力点,并剖析了大数据技术在地理信息产业的相关应用中所面临的制约因素。     

CORS环境下GPS RTK测量时的坐标系统及相互转换

GPS定位技术已经被广泛地运用并发展成为一个真正的三维测量工具。GPS CORS系统是GPS的连续运行参考站,是在一个城市、一个地区、或一个国家范围内,根据要求按一定距离间隔,建立常年连续运行的若干个固定GNSS参考站,组成的网络系统。本文通过对GPSRTK测量中遇到的不同坐标系统的分析,阐明了不同坐标系统之间数据转换的本质。结合在生产中使用的GPSRTK设备,说明了WGS-84坐标系向地方坐标系转换的一般过程和注意事项;对GPSRTK测量中遇到的不同坐标系统,进行理论上和实践上的研究,达到了预期效果,掌握了中海达V8GNSS RTK接收机在GPSRTK测量中的使用问题。