针对实际飞机电源系统部分电缆以多股形式存在、无法实现在线诊断的研究现状,开展了基于扩展频谱时域反射法(spread spectrum time domain reflectometry,SSTDR)的多股电缆故障在线诊断方法研究。相对于成熟的单根电缆故障在线诊断基础...针对实际飞机电源系统部分电缆以多股形式存在、无法实现在线诊断的研究现状,开展了基于扩展频谱时域反射法(spread spectrum time domain reflectometry,SSTDR)的多股电缆故障在线诊断方法研究。相对于成熟的单根电缆故障在线诊断基础,分析了多股电缆诊断中由于信号汇流导致的误判问题,提出了利用阻波器及滤波算法结合的方法,消除了信号汇流对故障诊断产生的影响,并提出了多通道分时循环检测定位方法,简化诊断装置,减小了实际硬件的成本与体积。实验结果表明,在定位误差0.2 m内,多股电缆的检测率在90%以上,诊断效果较好。该方法具有很强的工程价值,对实际的应用具有理论指导意义。展开更多
The naive, Bayes （NB） model has been successfully used to tackle spare, and is very accurate. However, there is still room for improwment. We use a train on or near error （TONE） method in online NB to enhance the ...The naive, Bayes （NB） model has been successfully used to tackle spare, and is very accurate. However, there is still room for improwment. We use a train on or near error （TONE） method in online NB to enhance the perfornmnee of NB and reduce the number of training emails. We conducted an experiment to determine the performanee of the improved algorithm by plotting （I-ROCA）% curves. The resuhs show that the proposed method improves the performanee of original NB.展开更多
Context-aware is becoming standard on the most mobile navigation devices. The performance of MEMS IMU/GNSS gains significant benefits from context information in terms of improvement of filter＇ s adaptive capability....Context-aware is becoming standard on the most mobile navigation devices. The performance of MEMS IMU/GNSS gains significant benefits from context information in terms of improvement of filter＇ s adaptive capability. A context-aware algorithm using differential carrier phase was proposed to recognize a molile MEMS IMU/GNSS equipped vehicle＇ s stationary, slow moving or fast moving status. The corresponding context error in awarding was analyzed and consequently conducted two fading factors based on the analysis The factors were applied in the system＇ s adaptive filter with targeting applications in deep urban where severe multipath presents. The dense urban field test shows that the false alarm of proposed context-aware algorithm is less than 5% and the adaptive filtering can achieve around 15% improvement in terms of lo in two-dimension position accuracy.展开更多
基金supported by National Natural Science Foundation of China under Grant NO. 60903083Research fund for the doctoral program of higher education of China under Grant NO.20092303120005the Research Fund of ZTE Corporation
文摘The naive, Bayes （NB） model has been successfully used to tackle spare, and is very accurate. However, there is still room for improwment. We use a train on or near error （TONE） method in online NB to enhance the perfornmnee of NB and reduce the number of training emails. We conducted an experiment to determine the performanee of the improved algorithm by plotting （I-ROCA）% curves. The resuhs show that the proposed method improves the performanee of original NB.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61173076)
文摘Context-aware is becoming standard on the most mobile navigation devices. The performance of MEMS IMU/GNSS gains significant benefits from context information in terms of improvement of filter＇ s adaptive capability. A context-aware algorithm using differential carrier phase was proposed to recognize a molile MEMS IMU/GNSS equipped vehicle＇ s stationary, slow moving or fast moving status. The corresponding context error in awarding was analyzed and consequently conducted two fading factors based on the analysis The factors were applied in the system＇ s adaptive filter with targeting applications in deep urban where severe multipath presents. The dense urban field test shows that the false alarm of proposed context-aware algorithm is less than 5% and the adaptive filtering can achieve around 15% improvement in terms of lo in two-dimension position accuracy.
