电控柴油机EOL系统工艺建设的研究

介绍了电控柴油机EOL工位系统建设的解决方案,在生产线上使用EOL工具对电控柴油机ECU数据刷写的同时对柴油机进行故障诊断和故障清除,保存过程测试记录,并上传到服务器。实际使用表明,此EOL系统满足现代电控柴油机批量生产的需求。     

GF（2~m）域SM2算法的实现与优化

文章从有限域的基本运算和有限域上多倍点运算两个方面讨论分析了GF（2m）域SM2多倍点运算的实现算法和优化技巧,并给出了一个模一般三项式求余式的算法。实践表明运用这些算法和技巧,可以有效地提高多倍点运算的运行速度。     

有限状态变系数离散系统的稳定性检验

提出了系统参数独立于系统节拍变化的有限状态变系数离散系统模型、稳定性检验 定理及稳定性检验的快速算法.这类系统的稳定的充分必要条件是其传递函数的分母多项式 为有限Schur多项式簇.提出了改进的变系数Schur检验表,使系统的稳定性检验过程简化, 计算量大为减少,有限次运算即可完成.     

面向柔性客户需求的产品变型设计方法

针对柔性的客户定制需求,提出充分重用零件实例的产品变型设计方法.通过分析零件实例重用引起的尺寸约束冲突,提出基于尺寸变化概率和零件变型需求的尺寸约束冲突转移与延迟解决方案,并给出了尺寸变化概率和零件变型需求的统计模型;然后针对零件实例重用引起的客户需求损失提出定制特征指标的补偿作用,并以田口质量损失函数为基础构建了改进的客户需求损失综合模型.最后通过一个实例进行了验证,结果表明在产品变型设计过程中,选择对客户需求影响小的零件实例作为重用对象,可以实现在满足客户需求的同时有效地降低定制产品的成本、缩短交货期.     

基于光照方向估计的人脸图像阴影补偿

光照变化是影响人脸识别率的关键问题之一.人脸图像中的阴影严重影响了光照不变特征的有效提取.采用了一种基于光照方向估计的阴影补偿方法.因为人脸形状的相似性,某一点光源方向产生的阴影特性具有相似性.利用这一特性,首先通过子空间方法确定人脸图像的光源方向,然后再对该人脸图像进行相应的阴影补偿.在对人脸库YaleB和Extended YaleB （38人脸）的实验中表明,64种光源方向的识别率为96.8％.该方法能有效消除阴影便于后续光照不变特征的有效提取.     

面向产品变异设计的零件可拓物元模型研究

为满足产品变异设计的要求,提出了零件可拓物元模型结构.通过融合零件及其子结构的几何、结构关联关系、功能和语义等信息,建立了零件变异物元模型.结合可拓理论,研究了零件变异物元模型的可拓性,分析了零件变异物元模型对产品变异设计的支持情况.最后,基于零件变异物元模型,开发了产品变异设计原型系统,并以发动机曲轴零件为例,建立了零件可拓物元模型.实例证明,零件变异物元模型解决了产品变异设计引起的零件结构干涉和拓扑更新问题,为产品变异设计提供了条件.     

支持变型设计的可配置产品结构模型

根据变型设计对产品结构可配置性、可重用性和灵活性的需求,深入分析了广义产品结构和数据之间的语义关系,提出了一种将扩展与或树和装配有向图相结合的可配置产品结构模型。扩展与或树覆盖了一组变型产品的结构,建立了产品节点之间的内在语义关系和配置条件,用以支持变型产品的组成结构变型;装配有向图形式化描述装配关系和装配方向,用以表达产品结构中装配语义。在此基础上,通过可扩展属性集来描述产品结构中各节点属性及其关系,支持变型产品的参数变型与传递。最后以汽车减震器产品系列为例,说明该模型对支持快速变型设计的可行性。     

产品模块可拓变型设计方法

为更好地支持产品多样化设计,提出了一种基于功构变换的产品模块可拓变型设计方法.针对产品模块变型设计需求,采用功能-行为-结构的迭代映射方法,建立存在模块的功构分解模型.通过数学模型中功构的可拓变换与分解,建立期望模块的功构分解模型,并采用功能流和功能模型IDEF0相结合的功能建模方法,建立期望模块的功能模型;基于功能模型的约束,通过结构单元的删除和聚合,进行模块功构要素可拓变换的传导变换分析,展开期望模块功构综合与结构设计,从而实现模块的变型设计.将该方法应用于堆垛机推拉机构的变型设计,双倍程推拉机构变型为三倍程推拉机构,验证了该方法的可行性和有效性.     

Exergy and exergoeconomic analyses for integration of aromatics separation with aromatics upgrading

Methanol to aromatics produces multiple products, resulting in a limited selectivity of xylene. Aromatics upgrading is an effective way to produce more valuable xylene product, and different feed ratios generate discrepant product distributions. This work integrates the aromatics separation with toluene disproportionation, transalkylation of toluene and trimethylbenzene, and isomerization of xylene and trimethylbenzene. Exergy and exergoeconomic analyses are conducted to give insights in the splitting ratios of benzene, toluene and heavy aromatics for aromatics upgrading. First, a detailed simulation model is developed in Aspen HYSYS. Then, 300 splitting ratio sets of benzene and toluene for conversion are studied to investigate the process performances. The results indicate that there are different preferences for the splitting ratios of benzene and toluene in terms of exergy and exergoeconomic performances. The process generates lower total exergy destruction when the splitting ratio of toluene varies between 0.07 and 0.18, and that of benzene fluctuates between 0.55 and 0.6. Nevertheless, the process presents lower total product unit cost with the splitting ratio of toluene less than 0.18 and that of benzene fluctuating between 0.44 and 0.89. Besides, it is found that distillation is the biggest contributor to the total exergy destruction, accounting for 94.97%.     

β-Casein A1 and A2: Effects of polymorphism on the cheese-making process

Of late, “A2 milk” has gained prominence in the dairy sector due to its potential implications in human health. Consequently, the frequency of A2 homozygous animals has considerably increased in many countries. To elucidate the potential implications that beta casein (β-CN) A1 and A2 may have on cheese-making traits, it is fundamental to investigate the relationships between the genetic polymorphisms and cheese-making traits at the dairy plant level. Thus, the aim of the present study was to evaluate the relevance of the β-CN A1/A2 polymorphism on detailed protein profile and cheese-making process in bulk milk. Based on the β-CN genotype of individual cows, 5 milk pools diverging for presence of the 2 β-CN variants were obtained: (1) 100% A1; (2) 75% A1 and 25% A2; (3) 50% A1 and 50% A2; (4) 25% A1 and 75% A2; and (5) 100% A2. For each cheese-making day (n = 6), 25 L of milk (divided into 5 pools, 5 L each) were processed, for a total of 30 cheese-making processes. Cheese yield, curd nutrient recovery, whey composition, and cheese composition were assessed. For every cheese-making process, detailed milk protein fractions were determined through reversed-phase HPLC. Data were analyzed by fitting a mixed model, which included the fixed effects of the 5 different pools, the protein and fat content as a covariate, and the random effect of the cheese-making sessions. Results showed that the percentage of κ-CN significantly decreased up to 2% when the proportion of β-CN A2 in the pool was ≥25%. An increase in the relative content of β-CN A2 (≥50% of total milk processed) was also associated with a significantly lower cheese yield both 1 and 48 h after cheese production, whereas no effects were observed after 7 d of ripening. Concordantly, recovery of nutrients reflected a more efficient process when the inclusion of β-CN A2 was ≤75%. Finally, no differences in the final cheese composition obtained by the different β-CN pools were observed.