Neural network-based control for the fiber placement composite manufacturing process

At McDonnell Douglas Aerospace (MDA), an artificial neural network-based control system has been developed and implemented to control laser heating for the fiber placement composite manufacturing process. This neurocontroller learns the inverse model of the process on-line to provide performance that improves with experience and exceeds that of conventional feedback control techniques. When untrained, the control system behaves as a proportional-integral (PI) controller. However, after learning from experience, the neural network feedforward control module provides control signals that greatly improve temperature tracking performance. Faster convergence to new temperature set points and reduced temperature deviation due to changing feed rate have been demonstrated on the machine. A cerebellar model articulation controller (CMAC) network is used for inverse modeling because of its rapid learning performance. This control system is implemented in an IBM-compatible 386 PC with an A/D board interface to the machine. Work supported by the McDonnell Douglas Independent Research and Development Program Export Authority: 22CFR 125.4(b)(13)     

车联网中路边设施的分布式调度策略的研究

为了降低碳排放量和部署成本,利用太阳能给车联网路边设施(Road Side Unit, RSU)供电是一个可行的方法.本文针对太阳能供电的RSU,提出了两个分布式的在线调度策略,旨在最大化服务车辆数.在基于Markov链的调度策略中,采用Markov链表述RSU能量状态,并通过对动作的奖励最大化服务的车辆数;在基于阈值的调度策略中,RSU计算服务车辆时所消耗的能量,并结合自己的能量状态,选择服务的车辆.仿真结果表明,本文提出的在线调度策略增加了服务车辆数.     

基于水质模拟的水质在线监测站点布设研究

随着水质监测连续化的需求增加,河流水质在线监测站布设成为不可忽视的问题。本文采用水文模拟模型HSPF对台湾淡水河流域进行水量水质联合模拟。水文模拟以9个测站比对,纳什效率系数多数大于0.7;相关系数r皆大于0.7。水质模拟以27个测站比对,生化需氧量、氨氮、悬浮固体、溶氧的修正平均百分误差多数小于25%。基于水质变化率和水质超标率提出水质敏感河段概念,并以此确定为补充布设水质在线监测站点的优先河段。研究指出,淡水河流域水质在线监测站目前仍缺乏且位置不尽合理,应优先补充三峡河的三峡大桥、景美溪的宝桥、基隆河的江北桥水质在线监测站。     

基于长短期记忆网络的电网故障区域定位与故障传播路径推理

为了在发生故障后维持电力系统的安全稳定,有必要实现对故障区域的快速定位并确定故障冲击的传播路径,提出基于长短期记忆网络(LSTM)的故障区域定位和故障传播路径推理方法.首先,利用LSTM建立2个故障诊断模型分别实现在线检测故障时刻和确定故障区域;然后,通过计算故障点附近线路的端口供给能量确定故障冲击的传播路径;最后,以8机36节点电网为例进行算例验证,结果表明所提模型可在发生故障后短时间内检测到故障,给出故障区域和故障冲击传播的路径,且对噪声有较强的鲁棒性.     

基于电磁耦合注入的电力电缆局部缺陷在线定位方法

为了解决现有频域反射方法仅能在离线情况下对电缆缺陷进行定位检测的不足,提出了一种基于频域反射法和电磁耦合技术的电缆缺陷在线定位方法。首先,依据电缆分布参数模型对含有局部缺陷的电缆进行仿真建模,分析了不同电容变化程度的缺陷点与不同测试频率对电缆缺陷定位效果的影响。然后,探究了传感器结构对信号注入效率的影响。最后,分别在实验室105 m和500 m电力电缆上进行验证,在离线测试情况下,通过改变105 m电缆末端负载阻值,模拟不同电缆负载下的线路情况,并分析其对局部缺陷处和电缆末端处反射强度的影响。在带电测试情况下,通过串联谐振平台对500 m电缆进行通电,利用所提在线定位方法对该电缆进行测试,以检验所提方法的有效性。仿真及实验结果表明：相较于电缆离线定位测试方法,该方法能够在电缆通电的状态下,实现对电缆缺陷点的在线定位,且具有较高定位精度和识别灵敏度。     

碳酸锂在水和NaCl-KCl溶液体系中溶解度的在线测定

碳酸锂溶解度在工业结晶生产中是十分重要的基础数据。采用浸入式红外探头和拉曼探头在线监测溶液体系中CO₃^2-和碳酸锂的特征峰峰强的变化,依据Lambert-Beer定律得出溶液体系中实时在线测定碳酸锂的溶解度。通过在线测定,测得碳酸锂在氯化钠-氯化钾溶液（c_NaCl=0.446 6 mol/L,c_KCl=0.015 8 mol/L）中的溶解度高于在水中的溶解度值。实验测试出的水中碳酸锂的溶解度数据还能与Van′t Hoff方程较好地关联,进一步测算碳酸锂在其他温度下水中的溶解度值。此外,该方法测定的碳酸锂在水中的溶解度数据比文献值中采用重量分析法测试出的溶解度数据偏小,是因为测试装置不同造成的。     

在线监测结晶器调宽换向阀阀芯卡阻方法的实现

对某炼钢厂铸机结晶器在线调宽液压系统的工作原理进行了分析,并重点分析了调宽过程中换向阀阀芯卡阻的问题,针对该问题对其液压系统进行了改进,改进后可以在线监测换向阀阀芯是否卡阻。该改进的实施在减少结晶器在线调宽时发生漏钢故障方面起到了重要作用。     

用神经网络和随机复合形搜索实施在线优化

提出一种基于神经网络和随机复合形法搜索的在线稳态优化方法，并对某厂气体分馏装置的生产过程的优化问题进行测试，得出优化操作条件。     

Guidelines for facilitating the development of learning communities in online courses

Online learning has grown exponentially in recent years; however, dropout problem remains challenging for some online programmes. The dropout problem can be attributed to a number of reasons, with a lack of interaction between learners and the instructor constituting one of the main reasons. The lack of interaction also leads to learners' feeling of isolation. Learning communities can provide learners with an environment conducive to increased interactions and alleviate their feeling of isolation. Unfortunately, there are no clear rules that instructors can follow to help learners create learning communities. In this paper, we propose guidelines for online instructors to facilitate the development of learning communities in online courses. We first review the definition of a learning community, importance of a learning community and factors affecting the development of a learning community. Afterwards, based on a review of the existing guidelines and other relevant literature, we propose guidelines for facilitating the development of learning communities in online courses.     

A novel method for camera external parameters online calibration using dotted road line

On board camera is the most important information source for driver assistant application which is based on computer vision. One problem for on board camera is that the external parameters are easy to be changed when moving on the road. Traditional method either calibrates external parameters offline or calibrates external parameters semi-online, which both need human intervention. By observation, it is found that corner connection of dotted road lane can form two groups of parallel lines. Using this geometric characteristics and through theoretical derivation, a novel online camera external parameter calibration method is proposed which focus on the situation when vehicle is moving. The pro of this method is that it maintains relatively high calculation accuracy and more important, it does not require any human intervention in whole calibration process. Experimental and comparison results show that this method is simple and have accurate results which fully meet the requirements of practical application.