Tool path optimisation method for large thin-wall part of spacecraft

Roughing tool path of panel machining, which is a bottleneck of spacecraft production, should be optimised rapidly to shorten process time. This problem has a large solution space, and surface quality should be taken into account. The decision variables are cavity machining order, feed point and cutting direction of each cavity. Our problem is presented as an asymmetric general travelling salesman problem (AGTSP). A cluster optimisation-based hybrid max–tmin ant system (CO-HMMAS) is proposed, which solves two sub-problems as a whole. The oriented pheromone and dynamic heuristic information calculating methods are designed. We analyse the differences between one-stage and two-stage AGTSP local search heuristics and combine CO-HMMAS with them properly. An improved Global 3-opt heuristic suitable for both symmetric and asymmetric cases is proposed with sharply reduced time complexity. Comparison experiments verified that, two-stage local search heuristics decrease solution error significantly and rapidly when the error is great, and one-stage ones improve a near-optimal solution costing much more computing time. Benchmarks tests show that, CO-HMMAS outperforms the state-of-the-art algorithm on several technical indexes. Experiments on typical panels reveal that all algorithm improvements are effective, and CO-HMMAS can obtain a better tool path than the best algorithm within less CPU time.     

Simultaneous monitoring of origin and scale of a shifted exponential process with unknown and estimated parameters

The distribution of consumer lifetimes, high-voltage of current in semiconductor transistors, and the risk associated with monitoring health care often come with a threshold. A two-parameter (or shifted) exponential distribution is, in general, regarded as a better statistical model in such situations compared with a traditional (one-parameter) exponential model. Research on inferential problems associated with two-parameter exponential distributions, including monitoring schemes for the parameters of this model, is active. Currently, all existing monitoring schemes for origin and scale parameters of a shifted exponential distribution assume that the process parameters are known (Case-K). The actual values of the process parameters are, however, rarely known in practice. The traditional method of estimating parameters from a set of a (Phase-I) reference sample and plug them in for Phase-II monitoring affects the performance of a monitoring scheme. Skewed processes, like the two-parameter exponential process, exacerbate this problem. The present article shows that even a reference sample of size 50,000 cannot guarantee nominal in-control performances of monitoring schemes when the actual process parameters are unknown (Case-U). To address this problem, we develop monitoring schemes based on max and distance statistics for simultaneously monitoring the two parameters of a shifted exponential process in Case-U. We show that the proposed schemes perform well. We illustrate the practical application of the proposed procedures by analyzing data about the production of an electronic component.     

Parallel variable neighborhood search for the min–max order batching problem

Warehousing is a key part of supply chain management. It primarily focuses on controlling the movement and storage of materials within a warehouse and processing the associated transactions, including shipping, receiving, and picking. From the tactical point of view, the main decision is the storage policy, that is, to decide where each product should be located. Every day a warehouse receives several orders from its customers. Each order consists of a list of one or more items that have to be retrieved from the warehouse and shipped to a specific customer. Thus, items must be collected by a warehouse operator. We focus on situations in which several orders are put together into batches, satisfying a fixed capacity constraint. Then, each batch is assigned to an operator, who retrieves all the items included in those orders grouped into the corresponding batch in a single tour. The objective is then to minimize the maximum retrieving time for any batch. In this paper, we propose a parallel variable neighborhood search algorithm to tackle the so‐called min–max order batching problem. We additionally compare this parallel procedure with the best previous approach. Computational results show the superiority of our proposal, confirmed with statistical tests.     

基于滑模状态观测器的永磁风电系统最大功率点跟踪控制策略

为了提高传统风能最大功率点跟踪控制的鲁棒性,提出了新的滑模自适应最大功率点跟踪控制策略。由于实际无速度传感器的风电系统变量难以测量,为此构造了滑模状态观测器来估计系统的转速跟踪误差,并基于估计值设计了滑模自适应最大功率点跟踪控制器。最后,基于MATLAB/Simulink仿真平台搭建了完整的风电系统仿真模型。仿真结果表明,在不同风速扰动作用下,所提出的控制策略均能实现良好的跟踪和控制效果,提高了风电系统的鲁棒性,保证了风电系统的最大功率输出。     

On Taylor series expansions for waiting times in tandem queues: an algorithm for calculating the coefficients and an investigation of the approximation error

Recently, a Taylor series expansion was developed for expected stationary waiting times in open (max,+)-linear stochastic systems with Poisson input process; these systems cover various instances of queueing networks.As an application, we present an algorithm for calculating the coefficients for infinite capacity tandem queueing networks with discrete service-time distributions. The algorithm works quite efficiently if the random vector of the service times of all servers is concentrated at a small number of atoms. We investigate the relative error of the Taylor approximation by simulation; in many cases, it follows very well a simple expression which holds exactly for independent, exponentially distributed servers.     

基于3D有限元模型的架空输电线路融冰电流计算

给出了架空输电线路直流融冰所涉及的两个重要参数:最小融冰电流和最大允许融冰电流的概念及计算方法。基于有限元法,以500kV架空输电线路常用的LGJ300/40钢芯铝绞线为模型,建立了覆冰导线3D热-电耦合仿真模型,计算出不同气候条件下、不同覆冰厚度的最小融冰电流,以及导线正常运行所允许的最大融冰电流,讨论了各种气候情况下融冰电流调节裕度,总结了最小融冰电流随环境条件和覆冰厚度的变化规律,可为运行人员提供重要的决策依据。     

中国东北地区大豆主要食叶害虫空间动态分析

对大豆蚜等7种食叶性害虫的田间分布型及其在豆株上的分布规律进行了系统研究。发生前期,大豆蚜Aphis glycines Masumura主要集中于植株上部叶片;发生中期,有向植株中、下部转移的趋势;后期,又迁至植株上部叶片危害。大豆蚜田间呈聚集分布型。茄无网长管蚜Acythosiphon solani（Kaltenbach）、二条叶甲Monolepta ni-grobilineata（Motsch.）成虫及豆卜馍夜蛾Bomolocha tristalis Lederer幼虫为全株发生。其中,二条叶甲成虫田间呈随机分布型。茄无网长管蚜发生前期至中后期,田间多呈聚集分布;发生后期,呈Poisson分布型。豆卜馍夜蛾幼虫发生前期,田间呈聚集分布;发生中后期,多呈均匀分布。豆黄蓟马Thrips nigropilosus Uzel若虫主要集中于植株上部发生,成虫全株发生。发生前期,豆黄蓟马为聚集分布;发生中期,成虫为均匀分布、若虫为聚集分布;发生后期,成虫为聚集分布、若虫为Poisson分布。双斑萤叶甲Monolepta hieroglyphica（Motsch.）成虫主要集中于植株上部发生,发生前期、后期,田间呈均匀分布型;发生中期,呈聚集分布型。发生前期及中期,大造桥虫Ascotis selenariaSchiffermüller et Denis幼虫主要于植株上部叶片发生,田间呈均匀分布型;发生后期,则转移至全株危害,呈Poisson分布型。     

大豆TPS基因家族全基因组鉴定、分类与表达分析

利用大豆基因组数据库,通过生物信息学分析,鉴定并获得大豆TPS家族基因所有成员的全序列、基因结构和定位信息。利用序列比对对大豆TPS家族基因进行进化和分类分析,同时通过soybase大豆发育表达芯片数据库相关信息,对该家族基因成员的组织表达谱进行了检测。研究结果表明,大豆基因组中含有20个TPS家族基因成员。系统发育分析将这些TPS基因分成了两个亚家族。基因定位分析表明,这些成员基因分别分布于大豆的14条染色体上。启动子分析表明,全部大豆TPS家族基因的启动子区都含有逆境反应顺式作用元件。转录水平芯片数据分析同时显示,大豆TPS家族基因大多在花、根、根瘤等组织中存在优势表达。该研究结果将促进大豆TPS家族基因的功能研究与利用。     

栽培大豆Rubisco小亚基基因（rbcS）全长cDNA的克隆及原核表达

根据NCBI中发表的大豆Rubisco小亚基基因（rbcS）序列（AF303939-1）设计特异引物,以吉农13大豆为实验材料,采用Trizol法提取叶片总RNA,通过RT-PCR克隆大豆rbcS的cDNA。将该基因与原核表达载体pET-30a（＋）连接,转化大肠杆菌E.coli BL21感受态细胞,双酶切鉴定后筛选阳性克隆,测序结果显示：rbcS全长696bp,其中开放阅读框为537bp,编码178个氨基酸;选择含大豆rbcS cDNA阳性克隆菌液IPTG诱导,经SDSPAGE分析,诱导表达出分子量为29.1kDa的融合蛋白,表达产物大小与预计理论值相符。诱导7h蛋白表达量最高,为64.15%。