基于雾气浓度估计的图像去雾算法

根据雾气浓度的视觉特征,提出一种雾气浓度估计模型.在此基础上,结合大气散射模型,提出一种新的图像去雾算法.首先,基于雾气浓度估计模型计算出雾气浓度量化图,利用模糊聚类算法在量化图中识别出雾气最浓区域并估计出全球光; 然后,对量化图中的“非雾气最浓”区域再次进行聚类处理,根据文中所提最优透射率评价指标估计出每个聚类单元的透射率,将全球光与透射图以及有雾图像导入散射模型,便可达到去雾的目的; 最后,针对去雾后图像较实际场景偏暗,提出一种基于小波域的多尺度锐化算法进行增强处理,以改善其主观视觉质量.实验结果表明,本文算法与现有主流算法相比,具有更好的去雾效果,并且其计算速度也相对较快.     

萤火虫算法智能优化粒子滤波

针对粒子滤波(Particle filter, PF)重采样导致的粒子贫化以及需要大量粒子才能进行状态估计的问题,本文结合粒子滤波的运行机制,对萤火虫算法的寻优方式进行修正,设计了新的萤火虫位置更新公式和荧光亮度计算公式,并在此基础上提出了萤火虫算法智能优化粒子滤波.该方法引入了萤火虫群体的优胜劣汰机制以及萤火虫个体的吸引和移动的行为,使粒子群智能地向高似然区域移动,提高了粒子群的整体质量.实验表明该方法提高了粒子滤波的预测精度,同时大大降低了状态值预测所需的粒子数量.     

Nonlinear aircraft sensor fault reconstruction in the presence of disturbances validated by real flight data

This paper proposes an approach for Inertial Measurement Unit sensor fault reconstruction by exploiting a ground speed-based kinematic model of the aircraft flying in a rotating earth reference system. Two strategies for the validation of sensor fault reconstruction are presented: closed-loop validation and open-loop validation. Both strategies use the same kinematic model and a newly-developed Adaptive Two-Stage Extended Kalman Filter to estimate the states and faults of the aircraft. Simulation results demonstrate the effectiveness of the proposed approach compared to an approach using an airspeed-based kinematic model. Furthermore, the major contribution is that the proposed approach is validated using real flight test data including the presence of external disturbances such as turbulence. Three flight scenarios are selected to test the performance of the proposed approach. It is shown that the proposed approach is robust to model uncertainties, unmodeled dynamics and disturbances such as time-varying wind and turbulence. Therefore, the proposed approach can be incorporated into aircraft Fault Detection and Isolation systems to enhance the performance of the aircraft.     

采用双状态传播卡方检验和模糊自适应滤波的容错组合导航算法

太阳能高空长航时无人机导航系统中,捷联惯导/北斗2κ全球卫星导航/星光导航(SINS/BD2/GPS/CNS)是一种可用的组合方案.针对常规容错组合导航算法故障检测类型单一,故障时滤波精度下降的问题,提出一种采用双状态卡方检验(TSPCST)和模糊自适应滤波(FAF)的容错组合导航算法.为了同时检测多种故障,将TSPCST应用于联邦滤波结构中;为了防止故障数据污染系统,利用FAF输出的高精度导航信息,对双状态传播器定期交替校正;进一步,FAF运用TSPCST检测得到的故障信息变量,定义量测子系统模糊有效域,将检测阈值模糊化,以弥补常规固定检测阈值算法难以选取阈值的不足;最后,通过计算信息分配因子,自适应处理多种故障数据.仿真结果表明,该容错组合导航算法性能优于常规固定检测阈值算法.     

中医针灸领域术语自动抽取研究

针对中医针灸领域术语的构成特点,该文建立了一种基于规则的领域术语抽取算法模型,该模型首先对中医针灸领域术语种子集进行有限次的迭代,生成中医针灸领域术语构件集;然后,以术语构件集为领域词典,采用最大向前匹配算法对中文针灸医学文献中的句子进行切分,并抽取候选术语;最后,利用语言规则对候选术语进行过滤处理,筛选出中医针灸领域专业术语。分别以关键字集和中医词典为种子集进行实验,开式测试的F值分别达到76.96%和35.59%。
     

基于图像受噪程度的改进模糊加权均值滤波

根据高斯噪声密度大、噪声强度的波动范围宽,其污染图像不仅每一个像素灰度级都会受影响,而且即使是同一灰度级受污染的程度也会不同的特点和传统的图像模糊滤波算法在图像细节保护方面上的不足,提出基于图像受噪程度的改进模糊加权均值滤波算法,该算法根据图像各像素点的受噪程度,得到首次滤波图像和原图像估计直方图,根据该直方图确定模糊隶属度函数,然后对首次滤波图像中灰度小于25的像素点进行模糊加权均值滤波,该算法在不需要期望图像和高斯噪声方差的情况下能有效地去除噪声,同时能够很好地保护图像细节信息。     

Robust periodically time‐varying horizon finite memory fault detection filter design for polytopic uncertain discrete‐time systems

In this paper, a robust periodically time‐varying horizon finite memory fault detection filter (PTVHFM‐FDF) is proposed to generate residual signal for the purpose of system monitoring. The major advantage of PTVHFM‐FDF is that finite historical data can be sufficiently utilized to enhance the robustness of fault detection against model uncertainty and external disturbance. The analysis, design, and application of PTVHFM‐FDF consist of several steps. Firstly, a periodic time‐varying residual error system is constructed on the basis of augmented method and time domain partition method. Secondly, in facilitating robust stability and performance analysis, the time‐varying residual error system is further transformed into a polyhedral time‐invariant system on the basis of time lifting technique. Thirdly, less conservative PTVHFM‐FDF analysis and design conditions are then obtained on the basis of Finsler relaxation lemma and slack variable structure definition. Fourthly, choices of memory window horizon parameters are properly suggested on the basis of a compromise between FDF robustness and its structural complexity. Finally, an integrated design and application algorithm of PTVHFM‐FDF is summarized. Effectiveness of PTVHFM‐FDF is verified through three examples. Copyright © 2017 John Wiley & Sons, Ltd.     

Time–frequency localized three-band biorthogonal wavelet filter bank using semidefinite relaxation and nonlinear least squares with epileptic seizure EEG signal classification

In this paper, we design time–frequency localized three-band biorthogonal linear phase wavelet filter bank for epileptic seizure electroencephalograph (EEG) signal classification. Time–frequency localized analysis and synthesis low-pass filters (LPF) are designed using convex semidefinite programming (SDP) by transforming a nonconvex problem into a convex SDP using semidefinite relaxation technique. Three-band parameterized lattice biorthogonal linear phase perfect reconstruction filter bank (BOLPPRFB) is chosen and nonlinear least squares algorithm is used to determine its parameters values that generate the designed analysis and synthesis LPF such that the band-pass and high-pass filters are also well localized in time and frequency domain. The designed analysis and synthesis three-band wavelet filter banks are compared with the standard two-band filter banks like Daubechies maximally regular filter banks, Cohen–Daubechies–Feauveau (CDF) biorthogonal filter banks and orthogonal time–frequency localized filter banks. Kruskal–Wallis statistical test is employed to measure the statistical significance of the subband features obtained from the various two and three-band filter banks for epileptic seizure EEG signal classification. The results show that the designed three-band analysis and synthesis filter banks both outperform two-band filter banks in the classification of seizure and seizure-free EEG signals. The designed three-band filter banks and multi-layer perceptron neural network (MLPNN) are further used together to implement a signal classifier that provides classification accuracy better than the recently reported results for epileptic seizure EEG signal classification.     

Development of a 3D HUD using a tunable bandpass filter for wavelength multiplexing

A 3D stereoscopic head‐up display using a tunable bandpass filter to perform left and right image spectral separation is presented. Using a single filter reduces the size and the cost of the head‐up display optical engine and enables each spectral band to be accurately tuned. Experiments performed on the first prototype demonstrate the ability to continuously tune the bandpass frequency on 30‐nm range while keeping a 20‐nm bandwidth. Such a system avoids the use of a bulky and costly rotating wheel and enables the use of holographic optical elements known to be wavelength selective.     

石油化工仪表防雷接地系统设计与实现

为了提高石油化工仪表的防雷安全性,进行防雷接地系统的优化设计,提出一种基于漏感和励磁电感增益分配和检波控制的防雷接地系统设计方法,基于麦克斯韦全电流定理,进行石油化工仪表防雷接地的电磁场分析,以双运放LM358放大器为核心进行石油化工仪表防雷接地系统电路设计,主要包括了交流放大器设计、滤波器设计、检波器设计和直流放大器设计,在检波设计中采用8阶高通滤波器(S3529)并联,提高防雷接地系统的输出运放性能,最后进行系统调试和电路测试,结果表明,采用该系统进行石油化工仪表防雷接地设计,防雷的阻带衰减大于51dB,对雷击信号具有较好的高通滤波和低通滤波性能,较好地保护了石油化工仪表安全。