基于多视图立体视觉的沙堆三维尺寸测量研究

利用从运动中恢复结构方法(SFM),提出了一种基于多视图立体视觉的沙堆三维重建及三维尺寸测量方法。首先根据SFM方法的求解不稳定特点,结合光束平差法对SFM求解过程进行分析及优化;其次针对SFM重建结果为稀疏点云的问题,利用基于面片的稠密重建算法重新生成稠密的三维点云,再利用泊松算法对密集点云进行三维曲面重建;最后获得模型的三维尺寸信息。对某建筑工地的沙堆进行了三维尺寸的测量实验,实验结果验证了该方法的有效及可行性,提高了重建能力及精度,同时考虑了目标实际测量误差与重建误差,能够满足实际智能测量的应用需求。     

A new territory and its pioneer: opening up a dominant research stream for a translational research area

Scientometrics - An academic pioneer makes many trials to find relations and results that were unknown before. The verified relations and repeatable results the pioneer finds guide followers to...     

搅拌式风力致热装置启动性能研究

搭建搅拌式风力致热试验台,以自制的2种致热器为研究对象,使其分别在3个不同平均角加速度24.92、14.66、8.04 rad/s2下启动。通过动态扭矩测试仪和数据采集仪测试记录致热器启动阶段的相关数据。结果表明:致热器启动时所需扭矩与角加速度的一次方、转速、叶片半径的二次方成正比,同时得出这些因素之间的关系式;满负荷时,启动扭矩会出现一个峰值,且角加速度越大峰值越大,自然风必须提供峰值以上的扭矩,否则装置无法启动。     

Fabrication and microwave absorption properties of magnetite nanoparticle–carbon nanotube–hollow carbon fiber composites

Absorbents with “tree-like” structures, which were composed of hollow porous carbon fibers (HPCFs) acting as “trunk” structures, carbon nanotubes (CNTs) as “branch” structures and magnetite (Fe₃O₄) nanoparticles playing the role of “fruit” structures were prepared by chemical vapor deposition technique and chemical reaction. Microwave reflection loss, permittivity and permeability of Fe₃O₄–CNTs–HPCFs composites were investigated in the frequency range of 2–18 GHz. It was proven that prepared absorbents possessed the excellent electromagnetic wave absorbing performances. The bandwidth with a reflection loss less than −15 dB covers a wide frequency range from 10.2 to 18 GHz with the thickness of 1.5–3.0 mm, and the minimum reflection loss is −50.9 dB at 14.03 GHz with a 2.5 mm thick sample layer. Microwave absorbing mechanism of the Fe₃O₄–CNTs–HPCFs composites is concluded as dielectric polarization and the synergetic interactions exist between Fe₃O₄ and CNTs–HPCFs.     

Origin of the temperature stability of dielectric constant in CaCu3Ti4O12

The temperature and dc bias stability of the dielectric constant and loss tangent of CaCu₃Ti₄O₁₂ samples sintered under different oxygen atmospheres are discussed. The results suggest that the metal-oxygen vacancy related defects not only provide the charge carriers for the conduction (defect doping) but also contribute to the huge permittivity in the way of defect dipoles repositioning under charge carrier hopping. The charge localization in a specific copper-oxygen vacancy defect complex is the reason of the huge and stable permittivity and low dielectric loss in the middle temperature range, 90 K-200 K (20 Hz), while the implementation of the large barrier layer height needs a contribution by the titanium oxygen vacancy related trap charges in the grain boundaries, which also lead to a second permittivity stable range in a higher temperature range 200 K–300 K.     

Capturing what human eyes perceive: A visual hierarchy generation approach to emulating saliency-based visual attention for grid-like urban street networks

Visual hierarchy is an important notion in urban imagery research. As the skeletons of cities, urban streets attract more attention from urban residents and street network hierarchies are important references for urban planning and urban studies. However, due to the characteristic of over-regularization, it is often difficult for humans to differentiate visual salience for grid-like street networks, resulting in the hierarchies of grid-like streets yielded by existing methods being prone to cause visual cognitive confusion. Therefore, in this study, we proposed a novel model to quantify the extent to which a street attracts human visual attention through emulating the visual attention mechanism that can capture the focus of relatively significant elements at different levels of perception. Using the natural street (also known as the stroke) as the sensor unit, the comprehensive visual salience (CVS) index combining the geometric competitive factors of natural streets at the local scale and psychological competitive factors of natural streets at the global scale is designed. Finally, the visual salience of the urban natural streets is ranked by these CVS scores and the visual hierarchy is derived by the head/tail breaks scheme. The model was applied to eight typical grid-like street networks and the results show that the performance of visual discrimination on street hierarchies is greatly improved. Our hierarchy generation method could effectively detect visually prominent streets for grid-like street networks and generate the visual hierarchies of grid-like street networks that conform to the hierarchies perceived by human eyes. These results would provide helpful suggestions in practical urban street network applications.     

Liquefaction behavior of fiber-reinforced calcareous sands in unidirectional and multidirectional simple shear tests

A study on the liquefaction resistance of calcareous sands reinforced with polypropylene fibers was reported. Stress-controlled cyclic simple shear tests were conducted on specimens prepared at a relative density of 50%, with and without fiber reinforcements. The liquefaction behavior was investigated by considering the effects of fiber contents ranging from 0% to 1%, fiber lengths varying from 3 mm to 12 mm and loading patterns. The results indicated that increasing fiber content and fiber length resulted in a decrease in the deformation, a reduction in pore pressure accumulation rate, and improved the liquefaction resistance of calcareous sands. Additionally, the risk of soil liquefaction could be significantly reduced when the fiber content was greater than 0.8%. The multidirectional loading had a considerable effect in reducing the liquefaction resistance compared to unidirectional loading. Further, the stiffness degradation of calcareous sands decreased with increasing fiber content and fiber length. The pore pressure generated in the cyclic tests was analyzed and was found to be affected by fiber content. A pore pressure prediction model was proposed to obtain the pore pressure characteristics of fiber-reinforced calcareous sands under various fiber content conditions.     

Comparative analysis on similarities and differences of hydrogen energy development in the World's top 4 largest economies: A novel framework

A low-carbon energy transition is permeating many industrialized countries due to the overuse of fossil fuels and the climate change. Some countries stress the hydrogen energy in optimizing their energy structures. This article examines both the markets and the policies of the hydrogen industry in the World's Top 4 largest economies. To make the comparative analysis more logical, a novel conceptual model for energy transition -- the institution-economics-technology-behavior framework -- has been adopted to make a multi-dimensional discussion. The results show that: (1) From the perspective of strategic intention, developing hydrogen energy is conductive to the energy transition. (2) From the horizontal comparison, each country has its own advantages, however, the main driving factors are different. (3) From the vertical comparison, the hydrogen energy development in each country is still in the stage of quantitative change, and the inflection point of qualitative change has not been reached yet.     

基于数据驱动建模的核电站一回路管道劣化趋势研究

提出一种基于管道状态数据的分析方法，可得到管道劣化趋势，有助于预防管道劣化引起的泄漏。具体方法是通过融合主观专家经验层次分析法和客观大数据分析熵权法的优点，定量地构建一回路管道的改进马氏距离健康度模型，进而应用融合卷积神经网络和长短期记忆神经网络的组合预测模型，对一回路管道未来的劣化泄漏情况做出趋势分析和预判。仿真结果表明，构建的健康度模型能够较好的反映出一回路管道的真实健康状态；组合 预测模型可以有效地预测一回路管道劣化泄漏的趋势，为保障设备的安全稳定运行提供 参考。     

Selection of features from power theories to compose NILM datasets

The load disaggregation concept is gaining attention due to the increasing need for optimized energy utilization and detailed characterization of electricity consumption profiles, especially through Nonintrusive Load Monitoring (NILM) approaches. This occurs since knowledge about individualized consumption per appliance allows to create strategies striving for energy savings, improvement of energy efficiency, and creating energy awareness to consumers. Moreover, by using feature extraction to devise energy disaggregation, one can achieve accurate identification of electric appliances. However, even though several literature works propose distinct features to be utilized, no consensus exists in the literature about the most appropriate set of features that ensure high accuracy on load disaggregation. Thus, beyond presenting a critical analysis of some significant features often selected in the literature, this paper proposes identifying the most relevant ones considering collinearity and machine learning algorithms. The results show that high-performance metrics can be achieved with fewer features than usually adopted in the literature. Moreover, it is demonstrated that the Conservative Power Theory can offer the most representative features for appliance identification, leading to efficient power consumption disaggregation.