基于关键水平的水下采油树预防性维修决策方法

为解决电液复合水下采油树在运行过程中工作环境恶劣且复杂、系统要求可靠性高、维修难度大且费用高的问题,建立基于伽马退化过程的水下采油树组件可靠度退化模型和考虑维修花费、停产损失在内的维修成本模型,建立水下采油树系统预防性维修优化目标体系,基于多目标粒子群优化算法对维修策略进行优化。建立的模型可有效描述水下采油树系统的工作特性,最优解能够满足在低维修成本的前提下系统高可靠性的工作要求。     

Personalized broad learning system for facial expression

Multimedia Tools and Applications - Understanding human emotions through facial expressions is key enabling technology for interactive robots. Most approaches of facial expression recognition are...     

A distributed energy system integrating SOFC-MGT with mid-and-low temperature solar thermochemical hydrogen fuel production

Solar thermochemical hydrogen production with energy level upgraded from solar thermal to chemical energy shows great potential. By integrating mid-and-low temperature solar thermochemistry and solid oxide fuel cells, in this paper, a new distributed energy system combining power, cooling, and heating is proposed and analyzed from thermodynamic, energy and exergy viewpoints. Different from the high temperature solar thermochemistry (above 1073.15 K), the mid-and-low temperature solar thermochemistry utilizes concentrated solar thermal (473.15–573.15 K) to drive methanol decomposition reaction, reducing irreversible heat collection loss. The produced hydrogen-rich fuel is converted into power through solid oxide fuel cells and micro gas turbines successively, realizing the cascaded utilization of fuel and solar energy. Numerical simulation is conducted to investigate the system thermodynamic performances under design and off-design conditions. Promising results reveal that solar-to-hydrogen and net solar-to-electricity efficiencies reach 66.26% and 40.93%, respectively. With the solar thermochemical conversion and hydrogen-rich fuel cascade utilization, the system exergy and overall energy efficiencies reach 59.76% and 80.74%, respectively. This research may provide a pathway for efficient hydrogen-rich fuel production and power generation.     

基于特征融合的中文简历解析方法研究

针对基于规则和统计的传统中文简历解析方法效率低、成本高、泛化能力差的缺点，提出一种基于特征融合的中文简历解析方法，即级联Word2Vec生成的词向量和用BLSTM（Bidirectional Long Short-Term Memory）建模字序列生成的词向量，然后再结合BLSTM和CRF（Conditional Random Fields）对中文简历进行解析（BLSTM-CRF）。为了提高中文简历解析的效率，级联包含字序列信息的词向量和用Word2Vec生成的词向量，融合成一个新的词向量表示；再由BLSTM强大的学习能力融合词的上下文信息，输出所有可能标签序列的分值给CRF层；再由CRF引入标签之间约束关系求解最优序列。利用梯度下降算法训练神经网络，使用预先训练的词向量和Dropout优化神经网络，最终完成对中文简历的解析工作。实验结果表明，所提的特征融合方法优于传统的简历解析方法。     

提高琅琊山选矿厂铁回收率试验

琅琊山选矿厂为了提高选铁回收率，进行了粗、精、扫选磁场强度试验及磨矿细度对铁回收的影响试验。结果表明：①增大扫选磁场强度可以提高精矿铁回收率0.37个百分点；扫选磁场强度从168 kA/m提高到240 kA/m，磁性铁回收率从89.79%提高到90.86%。②磁性铁主要以微细粒流失在尾矿中，回收难度极大。③以增大扫选磁场强度可提高铁回收率0.37个百分点计算，每年可增加销售收入约14.6万元，大半年即可收回设备改造投资。     

PET的紫外老化性能及机理研究

采用力学、紫外-可见光分析和热失质等测试手段研究了PET改性料的紫外老化性能及老化机理。结果表明:复合助剂的加入能显著提升体系的力学性能保持率,进而提升其紫外老化寿命,提升的幅度随复合助剂中耐紫外剂含量的增加而显著增加。DSC分析表明,随着复合助剂的引入和老化的进行,改性料结晶度增加。文中进一步讨论了PET改性料的紫外老化机理。紫外-可见光分析表明,紫外老化能产生醌类和双醌类物质,进而提升PET改性料的紫外吸收度。     

超高效液相色谱—串联质谱法快速同时检测茶叶中7种香料

基于超高效液相色谱—串联质谱(UHPLC-MS/MS),建立了同时检测茶叶中7种可能非法添加的香料(茴香烯、香豆素、胡椒酚甲醚、指甲花醌、甲基丁香酚、蒲勒酮和反式肉桂醛)的定性、定量方法。茶叶样品经过乙腈—水混合溶剂提取,涡旋振荡,适当稀释并加入无水硫酸钠、十八烷基键合硅胶(C₁₈)和N-丙基乙二胺(PSA)进行净化,涡旋离心后,上清液过膜待测。以Kinetex C₁₈色谱柱分离,在多反应检测扫描(MRM)模式下经MS/MS进行基质外标法定量检测。试验结果表明,7种目标物在0.8~1 600.0 μg/L范围内呈良好线性,线性相关系数(R2)均大于0.999。方法的检出限为0.02~0.03 mg/kg,定量限为0.05~0.10 mg/kg,平均回收率为82.5%~102.5%,日内、日间精密度分别小于16%和18%。该方法快速、可靠、灵敏度高,用于检测市面流通的100个茶叶样品,结果检出了反式茴香脑、香豆素和胡椒酚甲醚等物质,最大浓度值分别为65.0,2.0,72.2 mg/kg。