为研究自由飞行条件下给定间距的飞机碰撞风险评估问题,通过分析自由飞行下的飞机碰撞过程,分解碰撞事故发生过程,将与碰撞密切相关的风险因素或过程事件视为节点,并确定节点之间的关系,建立自由飞行状态下基于贝叶斯网络的碰撞风险模型...为研究自由飞行条件下给定间距的飞机碰撞风险评估问题,通过分析自由飞行下的飞机碰撞过程,分解碰撞事故发生过程,将与碰撞密切相关的风险因素或过程事件视为节点,并确定节点之间的关系,建立自由飞行状态下基于贝叶斯网络的碰撞风险模型;利用传统的位置误差模型,以及最大期望(EM)算法,求解节点事件的先验概率,导入贝叶斯网络模型,求得2架飞机碰撞风险。算例结果表明,用该模型计算出的碰撞风险与实际情况相符,算例中飞机之间保持8 n mile的间距是安全的;利用该模型可在满足安全目标水平条件下缩小最小安全间距,提高空域利用率。展开更多
Sea-crossing bridges have attracted considerable attention in recent years as an increasing number of projects have been constructed worldwide.Situated in the coastal area,sea-crossing bridges are subjected to a harsh...Sea-crossing bridges have attracted considerable attention in recent years as an increasing number of projects have been constructed worldwide.Situated in the coastal area,sea-crossing bridges are subjected to a harsh environment(e.g.strong winds,possible ship collisions,and tidal waves)and their performance can deteriorate quickly and severely.To enhance safety and serviceability,it is a routine process to conduct vibration tests to identify modal properties(e.g.natural frequencies,damping ratios,and mode shapes)and to monitor their long-term variation for the purpose of early-damage alert.Operational modal analysis(OMA)provides a feasible way to investigate the modal properties even when the cross-sea bridges are in their operation condition.In this study,we focus on the OMA of cable-stayed bridges,because they are usually long-span and flexible to have extremely low natural frequencies.It challenges experimental capability(e.g.instrumentation and budgeting)and modal identification techniques(e.g.low frequency and closely spaced modes).This paper presents a modal survey of a cable-stayed sea-crossing bridge spanning 218 m+620 m+218 m.The bridge is located in the typhoon-prone area of the northwestern Pacific Ocean.Ambient vibration data was collected for 24 h.A Bayesian fast Fourier transform modal identification method incorporating an expectation-maximization algorithm is applied for modal analysis,in which the modal parameters and associated identification uncertainties are both addressed.Nineteen modes,including 15 translational modes and four torsional modes,are identified within the frequency range of[0,2.5 Hz].展开更多
A new parallel expectation-maximization （EM） algorithm is proposed for large databases. The purpose of the algorithm is to accelerate the operation of the EM algorithm. As a well-known algorithm for estimation in ge...A new parallel expectation-maximization （EM） algorithm is proposed for large databases. The purpose of the algorithm is to accelerate the operation of the EM algorithm. As a well-known algorithm for estimation in generic statistical problems, the EM algorithm has been widely used in many domains. But it often requires significant computational resources. So it is needed to develop more elaborate methods to adapt the databases to a large number of records or large dimensionality. The parallel EM algorithm is based on partial Esteps which has the standard convergence guarantee of EM. The algorithm utilizes fully the advantage of parallel computation. It was confirmed that the algorithm obtains about 2.6 speedups in contrast with the standard EM algorithm through its application to large databases. The running time will decrease near linearly when the number of processors increasing.展开更多
We propose a robust visual tracking framework based on particle filter to deal with the object appearance changes due to varying illumination, pose variantions, and occlusions. We mainly improve the observation model ...We propose a robust visual tracking framework based on particle filter to deal with the object appearance changes due to varying illumination, pose variantions, and occlusions. We mainly improve the observation model and re-sampling process in a particle filter. We use on-line updating appearance model, affine transformation, and M-estimation to construct an adaptive observation model. On-line updating appearance model can adapt to the changes of illumination partially. Affine transformation-based similarity measurement is introduced to tackle pose variantions, and M-estimation is used to handle the occluded object in computing observation likelihood. To take advantage of the most recent observation and produce a suboptimal Gaussian proposal distribution, we incorporate Kalman filter into a particle filter to enhance the performance of the resampling process. To estimate the posterior probability density properly with lower computational complexity, we only employ a single Kalman filter to propagate Gaussian distribution. Experimental results have demonstrated the effectiveness and robustness of the proposed algorithm by tracking visual objects in the recorded video sequences.展开更多
文摘为研究自由飞行条件下给定间距的飞机碰撞风险评估问题,通过分析自由飞行下的飞机碰撞过程,分解碰撞事故发生过程,将与碰撞密切相关的风险因素或过程事件视为节点,并确定节点之间的关系,建立自由飞行状态下基于贝叶斯网络的碰撞风险模型;利用传统的位置误差模型,以及最大期望(EM)算法,求解节点事件的先验概率,导入贝叶斯网络模型,求得2架飞机碰撞风险。算例结果表明,用该模型计算出的碰撞风险与实际情况相符,算例中飞机之间保持8 n mile的间距是安全的;利用该模型可在满足安全目标水平条件下缩小最小安全间距,提高空域利用率。
基金supported by the Start-up Fund from Zhejiang University(No.130000-171207704/018)the National Natural Science Foundation of China(Nos.U1709207,51578506 and 51908494)。
文摘Sea-crossing bridges have attracted considerable attention in recent years as an increasing number of projects have been constructed worldwide.Situated in the coastal area,sea-crossing bridges are subjected to a harsh environment(e.g.strong winds,possible ship collisions,and tidal waves)and their performance can deteriorate quickly and severely.To enhance safety and serviceability,it is a routine process to conduct vibration tests to identify modal properties(e.g.natural frequencies,damping ratios,and mode shapes)and to monitor their long-term variation for the purpose of early-damage alert.Operational modal analysis(OMA)provides a feasible way to investigate the modal properties even when the cross-sea bridges are in their operation condition.In this study,we focus on the OMA of cable-stayed bridges,because they are usually long-span and flexible to have extremely low natural frequencies.It challenges experimental capability(e.g.instrumentation and budgeting)and modal identification techniques(e.g.low frequency and closely spaced modes).This paper presents a modal survey of a cable-stayed sea-crossing bridge spanning 218 m+620 m+218 m.The bridge is located in the typhoon-prone area of the northwestern Pacific Ocean.Ambient vibration data was collected for 24 h.A Bayesian fast Fourier transform modal identification method incorporating an expectation-maximization algorithm is applied for modal analysis,in which the modal parameters and associated identification uncertainties are both addressed.Nineteen modes,including 15 translational modes and four torsional modes,are identified within the frequency range of[0,2.5 Hz].
基金the National Natural Science Foundation of China(79990584)
文摘A new parallel expectation-maximization （EM） algorithm is proposed for large databases. The purpose of the algorithm is to accelerate the operation of the EM algorithm. As a well-known algorithm for estimation in generic statistical problems, the EM algorithm has been widely used in many domains. But it often requires significant computational resources. So it is needed to develop more elaborate methods to adapt the databases to a large number of records or large dimensionality. The parallel EM algorithm is based on partial Esteps which has the standard convergence guarantee of EM. The algorithm utilizes fully the advantage of parallel computation. It was confirmed that the algorithm obtains about 2.6 speedups in contrast with the standard EM algorithm through its application to large databases. The running time will decrease near linearly when the number of processors increasing.
基金supported by National Natural Science Foundation of China (No.40627001)the 985 Innovation Project on Information Technique of Xiamen University (2004–2008)
文摘We propose a robust visual tracking framework based on particle filter to deal with the object appearance changes due to varying illumination, pose variantions, and occlusions. We mainly improve the observation model and re-sampling process in a particle filter. We use on-line updating appearance model, affine transformation, and M-estimation to construct an adaptive observation model. On-line updating appearance model can adapt to the changes of illumination partially. Affine transformation-based similarity measurement is introduced to tackle pose variantions, and M-estimation is used to handle the occluded object in computing observation likelihood. To take advantage of the most recent observation and produce a suboptimal Gaussian proposal distribution, we incorporate Kalman filter into a particle filter to enhance the performance of the resampling process. To estimate the posterior probability density properly with lower computational complexity, we only employ a single Kalman filter to propagate Gaussian distribution. Experimental results have demonstrated the effectiveness and robustness of the proposed algorithm by tracking visual objects in the recorded video sequences.
