A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and...A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.展开更多
A fault injection model-oriented testing strategy was proposed for detecting component vulnerabilities.A fault injection model was defined,and the faults were injected into the tested component based on the fault inje...A fault injection model-oriented testing strategy was proposed for detecting component vulnerabilities.A fault injection model was defined,and the faults were injected into the tested component based on the fault injection model to trigger security exceptions.The testing process could be recorded by the monitoring mechanism of the strategy,and the monitoring information was written into the security log.The component vulnerabilities could be detected by the detecting algorithm through analyzing the security log.Lastly,some experiments were done in an integration testing platform to verify the applicability of the strategy.The experimental results show that the strategy is effective and operable.The detecting rate is more than 90%for vulnerability components.展开更多
针对动车组故障预测与健康管理(Prognostics and Health Management,PHM)实时海量数据解析处理与模型计算问题,提出一种基于流计算的动车组PHM模型处理框架。首先分析动车组车载数据处理流程,然后基于Spark Streaming给出动车组PHM模型...针对动车组故障预测与健康管理(Prognostics and Health Management,PHM)实时海量数据解析处理与模型计算问题,提出一种基于流计算的动车组PHM模型处理框架。首先分析动车组车载数据处理流程,然后基于Spark Streaming给出动车组PHM模型处理的总体框架。针对实时海量数据解析处理,首先分析解析前的车载数据结构,定义解析后的车载数据结构,然后设计通用化数据解析组件,给出流计算实现方式。针对模型计算,详细给出PHM模型的形式化定义,包括模型的基本信息、输入、输出和逻辑主体等,根据此定义设计模型通用组件,实现模型的快速研发、高效计算和统一应用。通过动车组PHM系统的有效应用,证明了该框架可以很好地满足海量数据的实时计算需求。展开更多
为了解决高比例分布式电源(distributed generation,DG)大规模并网后实时量测数目缺失、传统预测辅助状态估计方法(forecasting-aided state estimation,FASE)估计精度有限等问题,提出了基于改进Crossformer伪量测构建的主动配电网FASE...为了解决高比例分布式电源(distributed generation,DG)大规模并网后实时量测数目缺失、传统预测辅助状态估计方法(forecasting-aided state estimation,FASE)估计精度有限等问题,提出了基于改进Crossformer伪量测构建的主动配电网FASE方法。首先,基于最大信息系数法(maximal information coefficient,MIC)筛选出高相关性的输入特征,提高预测模型的精度;然后,通过全变差正则化技术(total variation regularized,TV)优化鲁棒主成分分析法(robust principal component analysis,RPCA),构建TRPCA层,并将其嵌入到Crossformer中,以填补Crossformer无法有效处理非高斯噪声的空白;最后,利用改进的预测模型进行超短期负荷预测,经潮流计算得到节点伪量测,在量测不足情况下补全缺失数据,并结合扩展卡尔曼滤波器(extended Kalman filter,EKF)进行状态估计。在IEEE 33节点和IEEE 118节点标准配电网上进行仿真测试,结果表明所提方法在估计精度和鲁棒性等方面具有一定优势,可为主动配电网FASE提供参考。展开更多
基金Project(51175159)supported by the National Natural Science Foundation of ChinaProject(2013WK3024)supported by the Science andTechnology Planning Program of Hunan Province,ChinaProject(CX2013B146)supported by the Hunan Provincial InnovationFoundation for Postgraduate,China
文摘A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.
基金Project(513150601)supported by the National Pre-Research Project Foundation of China
文摘A fault injection model-oriented testing strategy was proposed for detecting component vulnerabilities.A fault injection model was defined,and the faults were injected into the tested component based on the fault injection model to trigger security exceptions.The testing process could be recorded by the monitoring mechanism of the strategy,and the monitoring information was written into the security log.The component vulnerabilities could be detected by the detecting algorithm through analyzing the security log.Lastly,some experiments were done in an integration testing platform to verify the applicability of the strategy.The experimental results show that the strategy is effective and operable.The detecting rate is more than 90%for vulnerability components.
文摘针对动车组故障预测与健康管理(Prognostics and Health Management,PHM)实时海量数据解析处理与模型计算问题,提出一种基于流计算的动车组PHM模型处理框架。首先分析动车组车载数据处理流程,然后基于Spark Streaming给出动车组PHM模型处理的总体框架。针对实时海量数据解析处理,首先分析解析前的车载数据结构,定义解析后的车载数据结构,然后设计通用化数据解析组件,给出流计算实现方式。针对模型计算,详细给出PHM模型的形式化定义,包括模型的基本信息、输入、输出和逻辑主体等,根据此定义设计模型通用组件,实现模型的快速研发、高效计算和统一应用。通过动车组PHM系统的有效应用,证明了该框架可以很好地满足海量数据的实时计算需求。
文摘为了解决高比例分布式电源(distributed generation,DG)大规模并网后实时量测数目缺失、传统预测辅助状态估计方法(forecasting-aided state estimation,FASE)估计精度有限等问题,提出了基于改进Crossformer伪量测构建的主动配电网FASE方法。首先,基于最大信息系数法(maximal information coefficient,MIC)筛选出高相关性的输入特征,提高预测模型的精度;然后,通过全变差正则化技术(total variation regularized,TV)优化鲁棒主成分分析法(robust principal component analysis,RPCA),构建TRPCA层,并将其嵌入到Crossformer中,以填补Crossformer无法有效处理非高斯噪声的空白;最后,利用改进的预测模型进行超短期负荷预测,经潮流计算得到节点伪量测,在量测不足情况下补全缺失数据,并结合扩展卡尔曼滤波器(extended Kalman filter,EKF)进行状态估计。在IEEE 33节点和IEEE 118节点标准配电网上进行仿真测试,结果表明所提方法在估计精度和鲁棒性等方面具有一定优势,可为主动配电网FASE提供参考。
