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.     

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.     

慕课在基础教育中推进的对策研究

分析了互联网教育的发展现状,介绍了慕课在基础教育中推进的必要性,列举了慕课在基础教育中推进的障碍,最后论述了推进慕课在基础教育中应用的对策.     

一种Android终端控制物联网结点的技术应用

提出了一种对楼宇分体空调进行集中管理的方法,结合物联网的构成及实际应用模式,探索并将其理论方法引入到系统中来,构建了一个基于物联网的分体空调远程集中控制系统。通过Android终端设备,可对系统运行情况进行实时监控和管理。经实验测试验证,该集中控制节点及感知节点的设计满足系统的要求,可靠性高,成本低,功能强。     

基于Android的安防视频监控系统

安防监控是未来智慧城市的重要发展方向之一,基于Android的视频监控使安防应用更为便捷、智能。本系统采用高性能的ARM Cortex-A8处理器,在Android系统之上构建了一个安防视频监控系统。采用Android底层的Linux内核驱动实现视频数据的采集,并通过移植x264和JRTPLIB库实现了视频数据的H．264编码和RTP协议传输,保证了视频监控具有较好的实时性和可靠性。