基于 Hadoop 的分布式视频处理

中国科学院计算机网络信息中心与青海湖保护区管理局合作,共同建设了青海湖野外网络视频监控。如何高效地处理每天产出的超过 100GB 的视频数据成为了一个难题。现在的视频处理系统采用计算和存储相分离的架构,这需要配置较高的专门服务器进行支撑,本文基于廉价扩展性能较好的 Hadoop 平台对视频处理做出了分布式的实现,并对单个视频文件做出了分布式转码的实现。同时,本文将基于 Hadoop 的分布式视频处理的实现和基于 HTCondor 的分布式视频的批处理实现进行了对比,实验证明,在不损失视频处理效率的条件下,基于 Hadoop 的分布式视频处理的实现拥有分布式文件系统支撑、完善的任务监控等优势。     

以临界屈曲应变为判断依据的非开挖内衬修复设计改进方法

《城镇排水管道非开挖修复更新工程技术规程》(CJJ/T 210-2014)选取管道的长期弹性模量EL进行内衬修复设计,并规定EL为短期弹性模量Es的0.5倍,但是对于这一做法的理论依据仍然存在较多质疑,也导致设计过于保守。据此考虑引入临界屈曲应变理论,提出以内衬的临界屈曲应变εr为破坏判据,并选取管道短期弹性模量Es进行设计的改进方法。研究表明,改进后的设计方法能够保证内衬设计在理论上的正确性,满足内衬的长期强度要求,减小大约21%的内衬设计壁厚,能够有效降低工程成本。     

Model-based and Fuzzy Logic Approaches to Condition Monitoring of Operational Wind Turbines

 It is common for wind turbines to be installed in remote locations on land or offshore, leading to difficulties in routine inspection and maintenance. Further, wind turbines in these locations are often subject to harsh operating conditions. These challenges mean there is a requirement for a high degree of maintenance. The data generated by monitoring systems can be used to obtain models of wind turbines operating under different conditions, and hence predict output signals based on known inputs. A model-based condition monitoring system can be implemented by comparing output data obtained from operational turbines with those predicted by the models, so as to detect changes that could be due to the presence of faults. This paper discusses several techniques for model-based condition monitoring systems: linear models, artificial neural networks, and state dependent parameter "pseudo" transfer functions. The models are identified using supervisory control and data acquisition (SCADA) data acquired from an operational wind firm. It is found that the multiple-input single-output state dependent parameter method outperforms both multivariate linear and artificial neural network-based approaches. Subsequently, state dependent parameter models are used to develop adaptive thresholds for critical output signals. In order to provide an early warning of a developing fault, it is necessary to interpret the amount by which the threshold is exceeded, together with the period of time over which this occurs. In this regard, a fuzzy logic-based inference system is proposed and demonstrated to be practically feasible.     

Bandwidth Allocation with Minimum Rate Constraints in Cluster-based Femtocell Networks

 Inter-femtocell interference becomes serious when femtocells are densely deployed. To mitigate the inter-femtocell interference, this paper proposes a cluster-based bandwidth allocation algorithm. We create femtocell clusters by constructing a weighted interference graph and allocate bandwidth to each cluster based on a Nash bargaining solution (NBS). Simulation results show that the cluster-based bandwidth allocation algorithm can reduce the inter-femtocell interference and meet the minimum rate constraint of each cluster.     

Game‐Based Valley‐Fill Charging Coordination for Large‐Population Plug‐in Electric Vehicles

Charging coordination of large‐population autonomous plug‐in electric vehicles (PEVs) in the power grid can be formulated as a class of constrained optimization problems. To overcome the computational complexity, a game‐based method is proposed for the charging problems of the PEV population, which is composed of homogeneous subpopulations, such that individuals update their best charging strategies simultaneously with respect to a common electricity price determined by the total demand. To mitigate the oscillation behavior caused by the greedy behavior for the cheap electricity by individuals, a deviation cost is introduced to penalize against the deviation of the individual strategy from the average value of the homogeneous subpopulation. By adopting a proper deviation cost and following a best strategy update mechanism, the game systems may converge to the socially optimal valley‐fill Nash equilibrium. Simulation examples are studied to illustrate the results.     

Design optimization of a runflat structure based on multi-objective genetic algorithm

Runflat structure plays an important role in determining the sustainable mileage after the tire is shot. Lightweight, stiffness and strength are highly relevant to the overall performance of the structure. A parameterized model was built based on the full study of the structure, and a new adaptive meshing method is proposed to ensure the quality of the model. The accuracy of the new model was verified by comparing to the traditional finite element model. The parameter study was carried out to investigate the response of the performance and mass. Multi-objective optimization model was established by applying optimal Latin square design method and response surface model approach. Non-dominated sorting genetic algorithm-II (NSGA-II) was applied to obtain the optimization design. The results indicate that the combination of parameterized model and multi-objective genetic algorithms successfully achieve the goal of multi-objective optimization for mass and displacement while ensuring the stress. Meanwhile, the optimal topology, shape and thickness optimization for the runflat structure have been achieved at the same time.     

一种新的珍珠层厚度测量方法

珍珠层厚度是珍珠价值最主要的衡量指标之一,目前珍珠层厚度的无损测量方法主要采用光学相干层析成像技术和X射线技术;光学相干层析成像技术在实际测量时精度较低;在研究X射线测量原理的基础上,提出了一种新的珠层厚度测量方法;首先介绍了灰度图像的边缘识别算法和珍珠核、珍珠外圆度拟合算法,其次提出了一种引入对照机制的珍珠层测量算法,最后还对算法的误差进行了分析,算法的误差可以控制在0.02％以内;实际的测量也验证了该测量方法具有很高的精度.     

商用车在线故障诊断系统设计与实现

为方便商用车监测运行状态与故障诊断,设计了一种基于SAE J1939协议的在线故障诊断系统;搭建了以S3C6410为主控制器的嵌入式Linux系统平台,详细介绍了故障诊断系统的硬件、软件以及应用层设计方案;该系统能够在线解析和显示车辆报文信息,保存CAN网络接收到的报文;实验结果表明,该系统运行稳定,实时性好,能够满足车辆在线监视和诊断的需要.