Characteristics of coal sludge slurry prepared by a wet-grinding process

Coal sludge slurry(CSS) is an alternative fuel and a potential competitive method for sludge reduction.Based on the researches of coal water slurry, we studied CSSs by using a wet-grinding process with different types of regional municipal sludge(sludge) in an orthogonal experiment. The sludge type,sludge mixing proportion, dosage of dispersant, and grinding time were tested in this study. The results show that water content and its occurrence characteristics in the sludge have primary hindering influences on slurry ability. The range of fixed-viscosity concentrations with raw wet sludge is from 50.78%to 44.40%(by weight), while the range is from 53.35% to 51.51%(by weight) with dry sludge. All of the CSSs exhibit shear-thinning behaviors with different variation trends, especially the CSSs with more than 15%(by weight) raw wet sludge in it. Adding the same proportion of raw wet sludge increases the thixotropic properties of CSSs and the highest area of thixotropy loop is 3065 Pa/s, while the highest value of dry sludge is 1798 Pa/s. Hydrophilic group plays an important role in adsorbing water and building three-dimension networks with other particles, which is the main reason for CSS properties.Therefore, the mechanism can be used to find the way for making high quality CSS.     

Connecting parameters optimization on unsymmetrical twin-tower structure linked by sky-bridge

Based on a simplified 3-DOF model of twin-tower structure linked by a sky-bridge, the frequency response functions, the displacement power spectral density （PSD） functions, and the time-averaged total vibration energy were derived, by assuming the white noise as the earthquake excitation. The effects of connecting parameters, such as linking stiffness ratio and linking damping ratio, on the structural vibration responses were then studied, and the optimal connecting parameters were obtained to minimize the vibration energy of either the independent monomer tower or the integral structure. The influences of sky-bridge elevation position on the optimal connecting parameters were also discussed. Finally, the distribution characteristics of the top displacement PSD and the structural responses, excited by El Centro, Taft and artificial waves, were compared in both frequency and time domain. It is found that the connecting parameters at either end of connection interactively affect the responses of the towers. The optimal connecting parameters can greatly improve the damping connections on their seismic reduction effectiveness, but are unable to reduce the seismic responses of the towers to the best extent simultaneously. It is also indicated that the optimal connecting parameters derived from the simplified 3-DOF model are applicable for two multi-story structures linked by a sky-bridge with dampers. The seismic reduction effectiveness obtained varies from 0.3 to 1.0 with different sky-bridge mass ratio. The displacement responses of the example structures are reduced by approximately 22% with sky-bridge connections.     

Deformation transition of intact coal induced by gas injection

Gas migration in coal bed is a multiple-physical process, of which not only includes gas desorption/diffusion through coal matrix and gas Darcy flow through the cleat system, but also results in deform...     

Multi-sensor information fusion estimators for stochastic uncertain systems with correlated noises

The information fusion estimation problems are investigated for multi-sensor stochastic uncertain systems with correlated noises. The stochastic uncertainties caused by correlated multiplicative noises exist in the state and observation matrices. The process noise and the observation noises are one-step auto-correlated and two-step cross-correlated, respectively. While the observation noises of different sensors are one-step cross-correlated. The optimal centralized fusion filter, predictor and smoother are proposed in the linear minimum variance sense via an innovative analysis approach. To enhance the robustness and flexibility, a distributed fusion filter is put forward, which requires the calculation of filtering error cross-covariance matrices between any two local filters. To avoid the calculation of cross-covariance matrices, another distributed fusion filter is also presented by using the covariance intersection (CI) fusion algorithm, which can reduce the computational cost. A simulation example is given to show the effectiveness of the proposed algorithms.     

On Detectability and Observability of Discrete‐Time Stochastic Markov Jump Systems with State‐Dependent Noise

This paper mainly studies the notions of detectability and observability for discrete‐time stochastic Markov jump systems with state‐dependent noise. Two concepts, called “W‐detectability” and “W‐observability,” for such systems are introduced, and are shown to coincide with the other concepts on detectability and observability reported recently in literature. Moreover, some criteria and interesting properties for both W‐detectability and W‐observability are obtained.     

Interest point detection using imbalance oriented selection

Interest point detection has a wide range of applications, such as image retrieval and object recognition. Given an image, many previous interest point detectors first assign interest strength to each image point using a certain filtering technique, and then apply non-maximum suppression scheme to select a set of interest point candidates. However, we observe that non-maximum suppression tends to over-suppress good candidates for a weakly textured image such as a face image. We propose a new candidate selection scheme that chooses image points whose zero-/first-order intensities can be clustered into two imbalanced classes (in size), as candidates. Our tests of repeatability across image rotations and lighting conditions show the advantage of imbalance oriented selection. We further present a new face recognition application—facial identity representability evaluation—to show the value of imbalance oriented selection.     

基于智能软开关的三相不平衡配电网动态重构策略

针对单相分布式电源（DG）的接入会加剧配电网不平衡程度、增大网络损耗,且在严重不平衡时影响系统安全运行的问题,提出计及智能软开关（SOP）的三相不平衡配电网动态重构策略。首先,构建考虑SOP和DG电流不平衡度约束的三相不平衡配电网动态重构模型;然后,针对模型的非凸性将原模型转化为混合整数线性规划模型;最后,对改进的IEEE34节点配电网和某地78节点实际配电网进行算例分析,结果表明所提模型和策略可在保证配电网的安全运行的同时提升配电网的经济效益。     

RTDNet：面向高分辨率卫星影像的赤潮探测网络

目的 赤潮是一种常见的海洋生态灾害,严重威胁海洋生态系统安全。及时准确获取赤潮的发生和分布信息可以为赤潮的预警和防治提供有力支撑。然而,受混合像元和水环境要素影响,赤潮分布精细探测仍是挑战。针对赤潮边缘探测的难点,结合赤潮边缘高频特征学习与位置语义,提出了一种计算量小、精度高的网络模型RTD-Net （red tide detection network）。方法 针对赤潮边缘探测不准确的问题,设计了基于RIR （residual-in-residual）结构的网络,以提取赤潮边缘水体的高频特征;利用多感受野结构和坐标注意力机制捕获赤潮水体的位置语义信息,增强赤潮边缘水体的细节信息并抑制无用的特征。结果 在GF1-WFV （Gaofen1 wide field of view）赤潮数据集上的实验结果表明,所提出的RTDNet模型赤潮探测效果不仅优于支持向量机（support vector machine,SVM）、U-Net、Deep-Labv3+及HRNet （high-resolution network）等通用机器学习和深度学习模型,而且也优于赤潮指数法GF1_RI （Gaofen1 red tide index ）以及赤潮探测专用深度学习模型RDU-Net （red tide detection U-Net）,赤潮误提取、漏提取现象明显减少,F1分数在两幅测试图像上分别达到了0.905和0.898,相较于性能第2的模型DeepLabv3+提升了2%以上。而且,所提出的模型参数量小,仅有2.65 MB,约为DeepLabv3+的13%。结论 面向赤潮探测提出一种基于RIR结构的赤潮深度学习探测模型,通过融合多感受野结构和注意力机制提升了赤潮边缘探测的精度和稳定性,同时有效降低了计算量。本文方法展现了较好的应用效果,可适用于不同高分辨率卫星影像的赤潮探测。     

水下光声图像空间配准算法研究综述

水下光声图像配准是水下设备实现信息融合的关键技术。在简述了水下光声图像配准的概念及实例的基础上,分析了目前水下光声图像重建与复原的相关算法,详细综述了水下异源图像基于区域和特征的配准算法研究进展,重点论述了基于图像域和形状特征相似度的两个准确度较高的研究方向的发展现状,并根据其他领域的异源图像配准的研究热点,从增加成像模型的结构性约束、引入相位一致性和生成对抗网络等算法提高配准精度,展望了水下声光图像配准研究的发展趋势。