基于光谱分类模型的保险杠物证无损研究

采用中红外光谱结合化学计量学的方法对车用保险杠碎片进行鉴别，分别对52个车用保险杠碎片样本的全波段光谱数据、指纹区光谱数据和主成分分析降维后的光谱数据建立Fisher判别分析和K近邻算法2种分类模型，并对分类结果进行比较。结果表明，主成分分析提取特征变量后构建的分类模型，分类的准确率更高，对聚丙烯（PP）、PP/滑石粉、PP/滑石粉/碳酸钙（CaCO₃）3种类型的样本分类准确率达到92.3 %，对PP/滑石粉类型中的10种品牌样本分类准确率达到88.9 %，分类结果理想；在构建的2种分类模型中，Fisher判别分析模型的分类率远高于K近邻算法模型，分析认为K近邻算法模型受到样本不均衡的影响；中红外光谱结合化学计量学可以实现对车用保险杠碎片的准确区分，且满足快速、无损的检验要求。     

基于彩色图像处理的浮选尾煤灰分软测量研究

浮选尾煤灰分是浮选产品的一个重要指标。针对选煤厂浮选尾煤灰分多采用离线检测而无法实现在线准确测量，以及当前浮选软测量多采用单一的灰度图像从而导致软测量模型精度及适应性较差的问题，提出了一种基于彩色图像处理的浮选尾煤软测量方法，建立了基于最小二乘支持向量机(LSSVM)的浮选尾煤灰分软测量模型。模型以不同颜色空间的彩色特征、灰度均值以及浓度特征为输入变量，以尾煤灰分作为输出变量，采用粒子群优化算法对LSSVM模型参数进行优化。结果表明：所建立的尾煤灰分软测量模型可以较好地实现浮选尾矿灰分的在线预测，引入浮选尾矿图像的彩色特征可以提高尾煤图像分析的精度，预测精度达96.89%。研究成果在柳湾选煤厂现场应用，并取得了较好的尾矿灰分测量效果。     

载人航天器环热控一体化仿真分析

采用系统建模及仿真方法搭建了一种典型载人航天器环热控一体化系统模型，分析了系统的性能。针对3人7天载人飞行工况开展了仿真分析，结果表明，经过合理设计，该系统可将舱内温湿度、压力、氧分压等参数控制在航天医学指标要求范围内。环热控系统仿真结果较好地预测了系统工作过程，显示了主要参数的变化情况，结果合理，验证了仿真方法、系统仿真模型的正确性。通过控制流体回路外回路旁通阀门开度，可准确控制外回路控温点温度，保证舱内温湿度在合理范围之内。此外，外回路控温点的设定会对环热控系统状态带来影响，通过合理设计外回路控温点，可保证舱内温湿度满足航天医学指标要求。     

Asynchronous adaptive output feedback sliding mode control for Takagi-Sugeno fuzzy Markovian jump systems with actuator faults

In this article, the problem of asynchronous adaptive dynamic output feedback sliding mode control (SMC) for a class of Takagi-Sugeno (T-S) fuzzy Markovian jump systems (MJSs) with actuator faults is investigated. The asynchronous dynamic output feedback control strategy is employed, as the nonsynchronization phenomenon of jump modes exists between the plant and the controller. A novel asynchronous adaptive SMC approach is proposed to solve the synthesis problem for T-S fuzzy MJSs with actuator faults. Sufficient conditions for stochastic asymptotic stability of T-S fuzzy MJSs are given. Under the designed asynchronous adaptive SMC scheme, the effects of actuator faults and external disturbance can be completely compensated and the reachability of sliding surface is ensured. Finally, an example is provided to demonstrate the effectiveness of the proposed design techniques.     

316L不锈钢non-Masing特性分析和疲劳寿命预测

对316L不锈钢在不同应变范围下分别进行了293 K和873 K试验温度下的低周疲劳试验，讨论了材料循环特性的幅值相关性和温度相关性，比较了不同条件下non-Masing特性，并利用能量方法进行了低周疲劳寿命预测。实验结果表明, 在不同条件下，循环初期会出现不同程度的循环硬化现象，随后会出现循环软化、饱和直至材料失效；与873 K 试验条件相比，材料在293 K温度下的non-Masing特性更为显著；在大应变范围下，两温度下材料的non-Masing特性更加明显。采用能量方法进行疲劳寿命预测时，预测结果均位于两倍分散带内，且基于non-Masing特性得到了比基于Masing特性更为精确的预测结果。在873 K温度和大应变范围下，显著的动态应变时效效应导致考虑non-Masing与Masing特性的预测结果相差不大。     

分时电价下多目标绿色可重入混合流水车间调度

针对多目标绿色可重入混合流水车间调度问题（RHFSP）的特点，在机器分配和工序排序的基础上引入分时电价机制，构建了以最小化最大完工时间、总能耗成本和碳排放为目标的绿色调度优化模型，提出了一种改进的多目标文化基因算法（MOMA）来求解该问题，通过数值实验验证了所设计的MOMA算法的可行性。实验结果表明MOMA算法在非劣解的收敛性、多样性和支配性指标方面都显著优于多目标蚁狮优化算法(MOALO)、多目标粒子群优化算法（MOPSO）和带精英策略的非支配排序遗传算法（NSGA-Ⅱ），四种算法的分布性指标无显著差异。所提出的模型能够使企业有效避开高电价时段作业，合理转移用电负荷，达到降低总用电成本和碳排放的目的。     

大采高综放工作面强动压端头顶板控制技术

为了解决大采高综放工作面回风侧端头顶板控制问题,针对马道头矿8211工作面的地质情况,通过对回风顺槽超前注浆加固,提高超前支护范围和支护强度,并对回风侧端头三角区煤壁和顶板进行化学浆加固的技术方案,有效控制了顺槽超前区围岩变形和工作面回风侧端头三角区煤壁片帮,保证了工作面端头区顶板安全。     

Hierarchical Learning Water Cycle Algorithm

In order to improve the global searching ability of Water Cycle Algorithm (WCA), the hierarchical learning concept is introduced and the Hierarchical Learning WCA (HLWCA) is proposed in this paper. The underlying idea of HLWCA is to divide the solutions into collections and give these collections with hierarchy differences. One of the collections has a higher hierarchy than others and utilizes an exploration-inclined updating mechanism. The solutions in this high hierarchy collection are the exemplars of other collections. The other collections are sorted according to the exemplars’ function value and the solutions in these collections actively choose whether to follow their own exemplar or not. Through different updating mechanisms of collections, the global searching ability is improved while the fast convergence and strong local search ability of WCA are retained. The proposed HLWCA is firstly experimented on IEEE CEC 2017 benchmark suite to testify its performance on complex numerical optimization tasks. Then, it is tested on four practical design benchmark problems to verify its ability of solving real-world problems. The experimental results illustrate the efficiency of the proposed algorithm.     

Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions

The minimum cost flow problem (MCFP) is the most generic variation of the network flow problem which aims to transfer a commodity throughout the network to satisfy demands. The problem size (in terms of the number of nodes and arcs) and the shape of the cost function are the most critical factors when considering MCFPs. Existing mathematical programming techniques often assume the cost functions to be linear or convex. Unfortunately, the linearity and convexity assumptions are too restrictive for modelling many real-world scenarios. In addition, many real-world MCFPs are large-scale, with networks having a large number of nodes and arcs. In this paper, we propose a probabilistic tree-based genetic algorithm (PTbGA) for solving large-scale minimum cost integer flow problems with nonlinear non-convex cost functions. We first compare this probabilistic tree-based representation scheme with the priority-based representation scheme, which is the most commonly-used representation for solving MCFPs. We then compare the performance of PTbGA with that of the priority-based genetic algorithm (PrGA), and two state-of-the-art mathematical solvers on a set of MCFP instances. Our experimental results demonstrate the superiority and efficiency of PTbGA in dealing with large-sized MCFPs, as compared to the PrGA method and the mathematical solvers.     

Dynamic tensile mechanical properties and failure mode of zirconium diboride-silicon carbide ceramic composites

Dynamic indirect tension experiments were performed on zirconium diboride-silicon carbide (ZrB₂−20%SiC) ceramic. Flattened Brazilian disc specimens of ZrB₂−20%SiC were prepared to conduct dynamic tensile tests using the modified Split Hopkinson pressure bar system. The tensile experiments were completed at the range of loading rates from 7.53 to 74.71 GP s⁻¹. The tensile experimental results revealed that the zirconium diboride-silicon carbide ceramic composite is rate-sensitive in terms of the tensile strength and failure mode. The dynamic tensile strength increases linearly with the loading rate and changes from 195 MPa at 7.53 GP s⁻¹ to 654 MPa at 74.71 GP s⁻¹. Moreover, the dynamic tensile strength decreases with the increase in critical fracture time, which conforms to Tuler and Butcher's fracture criterion. In dynamic experiments, a high-speed camera was used to examine the tensile failure process, and fragments were collected to analyze the dynamic tensile failure mechanism. The tensile fracture mode of ZrB₂−20%SiC obviously showed the sensitivity of the loading rate. The fragment size of ZrB₂−20%SiC ceramic decreased but the quantity of fragments increased as the loading rate increased.