Analog circuit intelligent fault diagnosis based on GKPCA and multi-class SVM approach

Analog circuits fault diagnosis is essential for guaranteeing the reliability and maintainability of electronic systems. In this paper, a novel analog circuit fault diagnosis approach is proposed based on greedy kernel principal component analysis (KPCA) and one-against-all support vector machine (OAASVM). In order to obtain a successful SVM-based fault classifier, eliminating noise and extracting fault features are very important. Due to the better performance of nonlinear fault features extraction and noise elimination as compared with PCA, KPCA is adopted in the proposed approach. However, when we adopt KPCA to extract fault features of analog circuit, a drawback of KPCA is that the storage required for the kernel matrix grows quadratically, and the computational cost for eigenvector of the kernel matrix grows linearly with the number of training samples. Therefore, GKPCA, which can approximate KPCA with small representation error, is introduced to enhance computational efficiency. Based on the statistical learning theory and the empirical risk minimization principle, SVM has advantages of better classification accuracy and generalization performance. The extracted fault features are then used as the inputs of OAASVM to solve fault diagnosis problem. The effectiveness of the proposed approach is verified by the experimental results.     

Optimization design of the angle detecting system used in the fast steering mirror

In this paper, in order to design a fast steering mirror (FSM) with large deflection angle and high linearity, a deflection angle detecting system (DADS) using quadrant detector (QD) is developed. And the mathematical model describing DADS is established by analyzing the principle of position detecting and error characteristics of QD. Based on this mathematical model, the variation tendencies of deflection angle and linearity of FSM are simulated. Then, by changing the parameters of the DADS, the optimization of deflection angle and linearity of FSM is demonstrated. Finally, a QD-based FSM is designed based on this method, which achieves ±2° deflection angle and 0.72% and 0.68% linearity along x and y axis, respectively. Moreover, this method will be beneficial to the design of large deflection angle and high linearity FSM.     

三峡升船机卷筒强度可靠度计算的随机有限元法

针对三峡升船机的卷筒要求高可靠性这一特点，提出用随机有限元法计算其强度的可靠度，以提高计算的准确性，对三峡升船机卷筒强度的可靠性设计提供了较为信服的依据。其中，根据其受载特点，考虑了节点载荷之间的相关性，并建立了采用板单元时结构可靠度的计算方法。     

挤压铸造ZA27合金大高径比铸件

通常挤压铸造仅适用于高径比小于3.5的铸件,研究大高径比铸件的挤压铸造将扩大这种先进铸造技术的应用范围.用试验和计算机模拟的方法,研究了高径比为7的ZA27合金铸件的力学性能、凝固过程中铸件内的温度、压力以及缩松的分布.结果表明,增加挤压铸造的压力不能有效地减少大高径比铸件的缩松缺陷;合理控制浇注温度和铸型预热温度能有效地消除大高径比铸件内的缩松,获得力学性能高且均匀的铸件.     

AZ31变形镁合金挤压成形工艺的研究

选择AZ31变形镁合金，设计了实心棒材、矩形和圆形截面薄壁空心型材试样，对坯料加热、模具预热、润滑剂、挤压比、挤压速度及挤压力等工艺问题与工艺参数，进行了系统的试验研究，总结了成形规律和确定工艺参数的方法，对生产应用将起到重要的参考作用。     

多层次模糊综合优选法确定二次变电所主接线方案

指出了二次变电所主接线方案的多层次模糊综合优选理论方法，提出了评价的指标集，给出了判矩阵及权重，并举例计算。     

一种混合优化算法及其性能

结合遗传算法、粒子群优化算法和免疫算法提出了一种实数编码的混合优化算法(IG-PSOA),该方法利用非线性竞争择优的交叉操作和粒子群进化操作来提高算法的搜索效率,通过免疫选择和募集新成员操作保证种群的多样性,以避免早熟和局部收敛。从理论上分析了算法的收敛性和计算复杂度;用数值试验的方法分析了算法的鲁棒性和参数的取值范围。对7个测试函数的数值试验表明,该算法不仅提高了算法的全局搜索能力,提高了收敛的速度,而且提高了求解的质量和优化结果的可靠性,是一种有潜力的优化方法。     

基于遗传算法的粗糙集混合数据属性约简

为了对现实中既含有离散数据又有连续数据,甚至还有模糊数据的决策系统进行属性约简,基于模糊等价关系建立粗糙集模型,用熵来度量粗糙集中的不可分辨能量并定义约简.提出用遗传算法来求解含混合数据的决策系统的约简,论述了适应度函数的选择,给出了算法的具体实现.对经典数据集和UC I机器学习数据库中5个数据库约简的结果证明了算法的有效性和可行性.     

松子 健康日料倡导者

来到松子料理店,正巧赶上他们的早会,井然而有序,在主管交代完相关工作后,大家各就各位,开始了一天忙碌的工作。而对于这家在1992年就创建的日本料理店来说,这样的场景已经往复了20余年。