8603工作面回采巷道支护方案优化及数值模拟

针对深部软岩巷道围岩变形量大,传统支护结构失效的问题,以煤峪口矿回采巷道为研究背景,综合应用数值模拟和工程实践对原支护方案下巷道破坏特征进行分析,提出采用中空注浆锚索进行补强支护,并采用FLAC3D分析了两种支护方案下巷道围岩的收敛量以及应力分布情况,得出了优化支护方案能够有效控制巷道围岩破碎程度,并通过工程实践得到验证。     

Qualitative analysis of fluid dynamics and heat transfer characteristics in porous structures towards aqueous phase reforming hydrogen production

Porous structure is commonly used as a catalytic support in the field of fixed-bed reactor for hydrogen production from methanol aqueous phase reforming. The fluid dynamics and heat transfer characteristics of the fluid in a specific porous structure are considered profound influences for catalytic reactions. This study presented a qualitative investigation on the flow and heat transfer characteristics of fluids in variable porous structures. Specifically, the discrete average interpolation method was employed to obtain the value of a continuous structure. From the results, using the area-average temperature equation was 11% (±1.5%) larger and precise than that from the previous work using traditional hydrodynamic equation. The proposed variable porous structure could not only increase the turbulence intensity of the fluid which could further enhance reaction mass transfer but also enhance the convective heat transfer of the fluidic reactants. Some of these findings could inspire the reactor design for improving catalytic efficiency of hydrogen production.     

高压压气机转子结构设计及改进方法

为提高设计效率并快速得到适于工程应用的高压压气机转子结构，以改型设计方法为基础对某高压压气机转子结构进行了详细设计，同时对结构改进方法进行了一定的探索。采用叶—盘耦合系统循环对称结构算法及整体转子系统二维轴对称结构算法进行强度设计及改进，前轴颈最大应力下降最多达26%；其次进行支承结构设计，计算校核母型机轴承承载能力。结果表明：轴向力安全裕度最小为28%，轴承寿命大于100 000 h；给出2种调整鼠笼厚度的估算方法用以指导三维有限元计算，同时计算得到前支承刚度；通过二维有限元分析模型计算转子的临界转速，仅将后轴承支承位置沿压气机轴线向后移动7.5 mm，全运行工况转速与第2阶临界转速的安全裕度由18.5%提高到21.2%。     

Efficient fault diagnosis method of PEMFC thermal management system for various current densities

The temperature of a fuel cell has a considerable impact on the saturation of a membrane, electrochemical reaction speed, and durability. So thermal management is considered one of the critical issues in polymer electrolyte membrane fuel cells. Therefore, the reliability of the thermal management system is also crucial for the performance and durability of a fuel cell system. In this work, a methodology for component-level fault diagnosis of polymer electrolyte membrane fuel cell thermal management system for various current densities is proposed. Specifically, this study suggests fault diagnosis using limited data, based on an experimental approach. Normal and five component-level fault states are diagnosed with a support vector machine model using temperature, pressure, and fan control signal data. The effects of training data at different operating current densities on fault diagnosis are analyzed. The effects of data preprocessing method are investigated, and the cause of misdiagnosis is analyzed. On this basis, diagnosis results show that the proposed methodology can realize efficient component-level fault diagnosis using limited data. The diagnosis accuracy is over 92% when the residual basis scaling method is used, and data at the highest operating current density is used to train the support vector machine.     

A combination of near-infrared hyperspectral imaging with two-dimensional correlation analysis for monitoring the content of biogenic amines in mutton

The study investigated the feasibility of using a combination of near-infrared hyperspectral imaging (NIR-HSI) with two-dimensional correlation (2DCOS) analysis for rapid and non-destructive determination of the content of biogenic amines in mutton during refrigerated storage. Total contents of biogenic amines (TBA) were used as the perturbation. By analysing the synchronous and asynchronous two-dimensional correlation spectra, sensitive variables that were closely related to TBA contents were obtained. The results showed that the wavelengths in the spectra range of 1002–1335 nm were the research area for the detection of TBA contents in mutton. The least-squares support vector machines (LSSVM) model based on effective wavelengths selected by competitive adaptive reweighted sampling (CARS) from 2DCOS analysis showed excellent results, with correlation coefficient in prediction (Rp) of 0.91, root mean square error in prediction (RMSEP) of 1.67 mg kg⁻¹ and the ratio of performance deviation (RPD) of 2.76. The research demonstrated that the combination of NIR-HSI and 2DCOS could be used as an effective method for monitoring the content of biogenic amines in mutton.     

A Review of Guidance Approaches in Visual Data Analysis: A Multifocal Perspective

Visual data analysis can be envisioned as a collaboration of the user and the computational system with the aim of completing a given task. Pursuing an effective system‐user integration, in which the system actively helps the user to reach his/her analysis goal has been focus of visualization research for quite some time. However, this problem is still largely unsolved. As a result, users might be overwhelmed by powerful but complex visual analysis systems which also limits their ability to produce insightful results. In this context, guidance is a promising step towards enabling an effective mixed‐initiative collaboration to promote the visual analysis. However, the way how guidance should be put into practice is still to be unravelled. Thus, we conducted a comprehensive literature research and provide an overview of how guidance is tackled by different approaches in visual analysis systems. We distinguish between guidance that is provided by the system to support the user, and guidance that is provided by the user to support the system. By identifying open problems, we highlight promising research directions and point to missing factors that are needed to enable the envisioned human‐computer collaboration, and thus, promote a more effective visual data analysis.     

基于间隔理论的过采样集成算法

针对传统集成算法不适用于不平衡数据分类的问题，提出基于间隔理论的AdaBoost算法（MOSBoost）。首先通过预训练得到原始样本的间隔；然后依据间隔排序对少类样本进行启发式复制，从而形成新的平衡样本集；最后将平衡样本集输入AdaBoost算法进行训练以得到最终集成分类器。在UCI数据集上进行测试实验，利用F-measure和G-mean两个准则对MOSBoost、AdaBoost、随机过采样AdaBoost（ROSBoost）和随机降采样AdaBoost（RDSBoost）四种算法进行评价。实验结果表明，MOSBoost算法分类性能优于其他三种算法，其中，相对于AdaBoost算法，MOSBoost算法在F-measure和G-mean准则下分别提升了8.4%和6.2%。     

基于流形学习的光学遥感图像分类

随着光学遥感图像技术的快速发展与广泛应用,对光学遥感图像的准确分类具有深远的研究意义。传统特征提取方式提取的高维特征中夹杂着许多冗余信息,分类过程可能导致过拟合现象,针对传统的线性降维算法不足以保持原始数据的内部结构,容易造成数据失真这一问题,提出基于流形学习的光学遥感图像分类算法。该算法首先提取出图像的SIFT特征,然后将流形学习运用于特征降维,最后结合支持向量机进行训练和识别。实验结果表明,在Satellite、NWPU和UCMerced实验数据中,冰川、建筑群和海滩分类精度得到了有效提高,达到85%左右;针对沙漠、岩石、水域等特殊环境遥感图像,分类精度提高了10%左右。总而言之,基于流形学习的分类算法对通过降维之后的数据能够保持在原高维空间中的拓扑结构,相似特征点能得到有效聚合,预防了"维数灾难",减少了计算量,保证了分类精度。     

Human–machine shared control for lane departure assistance based on hybrid system theory

To improve the human–machine cooperation of lane departure assistance system (LDAS), a human–machine shared control strategy based on hybrid system theory was proposed. By considering vehicle’s discrete and continuous states and time-varying longitudinal speed, the hybrid system was formalized as hybrid automaton, and the shared control strategy was built to govern the human–machine interaction. Robust gain-scheduling energy-to-peak method was adopted to design the assistance system controller. The D-stability of the system was also studied and guaranteed by solving the linear matrix inequality (LMI). The proposed human–machine shared control method was evaluated via the co-simulation of CarSim/Simulink and the hardware-in-loop (HIL) experiment. The results showed that the proposed approach can effectively keep the vehicle in lane and a good human–machine coordination was demonstrated.