Joint production and maintenance planning with machine deterioration and random yield

Production, yield and maintenance are three key components for sustaining the competitiveness of a manufacturing firm. In this paper, we investigate a joint production and maintenance planning problem in a periodic review environment subject to stochastic demand and random yields. The manufacturing system deteriorates from period to period according to a discrete-time Markov chain. The objective is to find an integrated lot sizing and maintenance policy for the system such that the aggregate cost associated with production, holding, backlogging and maintenance is minimised. We formulate this integrated planning problem as a Markov decision process and analyse the structural properties of the optimal policies. We prove that the optimal production and the maintenance policies both exhibit a control limit structure and show that the solution to the finite-horizon problems converges to that of the infinite-horizon problem.     

Uncertainty quantification of high‐dimensional complex systems by multiplicative polynomial dimensional decompositions

The central theme of this paper is multiplicative polynomial dimensional decomposition (PDD) methods for solving high‐dimensional stochastic problems. When a stochastic response is dominantly of multiplicative nature, the standard PDD approximation, predicated on additive function decomposition, may not provide sufficiently accurate probabilistic solutions of a complex system. To circumvent this problem, two multiplicative versions of PDD, referred to as factorized PDD and logarithmic PDD, were developed. Both versions involve a hierarchical, multiplicative decomposition of a multivariate function, a broad range of orthonormal polynomial bases for Fourier‐polynomial expansions of component functions, and a dimension‐reduction or sampling technique for estimating the expansion coefficients. Three numerical problems involving mathematical functions or uncertain dynamic systems were solved to corroborate how and when a multiplicative PDD is more efficient or accurate than the additive PDD. The results show that indeed, both the factorized and logarithmic PDD approximations can effectively exploit the hidden multiplicative structure of a stochastic response when it exists. Since a multiplicative PDD recycles the same component functions of the additive PDD, no additional cost is incurred. Finally, the random eigensolutions of a sport utility vehicle comprising 40 random variables were evaluated, demonstrating the ability of the new methods to solve industrial‐scale problems. Copyright © 2013 John Wiley & Sons, Ltd.     

Towards the Development of Flexible Non‐Volatile Memories

Flexible non‐volatile memories have attracted tremendous attentions for data storage for future electronics application. From device perspective, the advantages of flexible memory devices include thin, lightweight, printable, foldable and stretchable. The flash memories, resistive random access memories (RRAM) and ferroelectric random access memory/ferroelectric field‐effect transistor memories (FeRAM/FeFET) are considered as promising candidates for next generation non‐volatile memory device. Here, we review the general background knowledge on device structure, working principle, materials, challenges and recent progress with the emphasis on the flexibility of above three categories of non‐volatile memories.     

纵向地震作用下大跨三塔悬索桥伸缩缝处双边碰撞效应研究

相邻桥跨间的碰撞效应是引起大跨桥梁引桥落梁的重要原因,本文以一座大跨三塔悬索桥为研究对象,建立了复杂的桥梁结构空间动力分析模型,采用非线性动力时程分析法,详细分析了大跨三塔悬索桥伸缩缝处主、引桥相邻梁体间的双边碰撞对桥梁结构地震反应的影响规律,揭示大跨桥梁主、引桥结构振动周期比与碰撞效应的内在联系。研究结果表明：当一侧引桥基本周期小于或者接近主桥梁端位移控制振型周期,而另一侧引桥基本周期显著大于主桥周期时,双边碰撞使长周期侧的引桥固定墩墩底地震内力响应、梁端位移、梁体搭接长度以及主、引桥间相对位移响应显著增大,而使短周期侧引桥梁端位移、梁体搭接长度以及主、引桥间相对位移响应轻微减小。     

一种在线学习的目标跟踪与检测方法

针对现有在线学习跟踪方法缺乏监督机制的缺点,提出一种新的跟踪框架。以随机森林在线学习理论构造分类器作为目标检测器,用SURF特征点匹配方法作为目标跟踪器,跟踪过程中用可靠跟踪的结果形成对检测结果的监督机制,不对低置信度样本或错误样本进行学习,避免了分类器分类精度的逐渐下降,同时在跟踪失败时用目标检测器对目标进行重新捕获,形成跟踪、学习、检测三者有机结合的跟踪框架。对不同视频序列的测试结果表明,本文算法能有效避免目标出现较大外观变化或被大面积遮挡等复杂情况下的跟踪失败问题。     

一种基于图像分解的乱针绣模拟生成方法

常州乱针绣是一种具有地方文化特色的绣艺品种,亟待使用先进技术进行保护和传承.论文提出了一种基于图像分解的乱针绣艺术效果模拟生成方法:将图像分解成不同的对象区域、矢量场和图像细节信息后,通过一种多层绘制技术模拟乱针绣的多层叠加效果,同时,建立模拟乱针绣针法的针法库,为使绘制结果更具真实感,模拟单根绣线方法也一并提出.实验结果表明,该方法能有效再现乱针绣艺术效果,为乱针绣数字化传承技术研究奠定了基础.     

基于分段改进S变换和随机森林的复合电能质量扰动识别方法

各类分布式设备和智能设备接入电力系统,使得电力系统对电能的波动越来越敏感,这导致对电能质量扰动(PQD)的识别和处理变得越来越重要。通过将分段改进S变换(SMST)和随机森林(RF)算法相结合,提出了一种用于复杂噪声环境下PQD识别的新方法。首先,基于检测误差和峰度对SMST的不同频段进行分别调参,并使用SMST提取待检测信号的75种时频特征,构成原始特征集。然后,改进分类回归树(CART)的节点分裂过程,加入了离散值处理策略并使用Gini指数的下降作为新的节点分裂规则。同时,在下次节点分裂前,将基尼指数下降值为零的特征从特征集中删除。最后,使用改进的CART算法构建了RF分类器并对复合PQD信号进行分类。实验证明,在不同的信噪比条件下,新方法均能有效识别多数单一PQD信号和常见的双重复合PQD信号。虽然新方法在运行效率方面仍有一定的改进空间,但其在不同层面上的改进均能有效提升PQD识别精度,且平均分类精度明显高于各类传统PQD识别方法。     

一种提高平稳随机载荷识别精度的方法

针对动态随机载荷识别结果在固有频率附近因传递函数矩阵病态而出现载荷识别误差较大的问题,在逆虚拟激励法的基础上提出一种条件数加权平均算法尝试改善识别的精度。方法用仿真和试验验证了对识别精度的改善效果。同时采用频响函数条件数的大小来作为判断识别结果可靠度和测点组合选择的一个参考,减少了工作量并取得了良好的识别效果。提出了一些实际操作中的建议,为工程实际提供参考。     

机载多管火箭非满管射击试验方法研究

研究机载多管火箭非满管射击试验方法,为减少机载多管火箭密集度试验用弹量提供新的试验方法。应用发射动力学和多体系统传递矩阵法理论,基于等起始扰动思想,建立了机载多管火箭发射动力学模型、特征方程和动力响应方程,并应用随机整数规划方法,形成了减少机载多管火箭试验用弹量方法。针对某19管机载多管火箭,提出了6发连射的密集度试验方案,试验验证使密集度试验用弹量比常规试验方法减少了68.4%,节省了大量试验费用。     

恒力吊架力学性能对低温再热蒸汽管道热位移的影响

采用JY—20便携式测试系统,对某火电厂低温再热蒸汽管道恒力吊架的恒定度和载荷偏差进行了测试,探讨了恒力吊架力学性能对低温再热蒸汽管道热位移产生的影响。结果表明:恒力吊架载荷偏差及恒定度不合格是造成低温再热蒸汽管道无法复位的主要原因;更换性能合格的恒力吊架后,恒力吊架的位移指针基本能回复到原位,管道热位移正常,且各主要管种的最大一次应力和二次应力均在其允许值范围内。