检测传感器故障的鲁棒观测器

介绍一种在系统参数变化情况下进行故障检测的观测器。对观测器采用特征值、特征向量进行联合配置的算法 ,并对估计误差设计奇偶空间 ,使各传感器的故障在奇偶空间中被解耦分离 ,因而可用一个观测器检测与分离多路故障传感器 ,实现了故障检测的鲁棒性     

基于数据融合的MEMS阵列加速度传感器实现方法

针对单MEMS加速度计性能有限无法满足实际工程中日益复杂且严苛的检测需求的问题,提出了一种基于数据融合的MEMS阵列加速度传感器实现方法。首先,设计了MEMS阵列加速度传感器的系统架构,并分析了对数据融合算法的技术需求;然后,针对已有的数据融合技术无法满足MEMS阵列加速度传感器的精度与实时性要求的问题,提出了基于离散对数映射的自整定加权融合算法,在此基础上,设计了MEMS阵列加速度传感器的仿真验证方案。仿真实验结果表明,提出的方法通过三个不同范围MEMS加速度计的阵列集成提高了信号检测能力,相比于最优拼接法其平均损失降低了6.1%,且融合数据精度优于各个加速度传感器的原始仿真数据,是高性能MEMS阵列加速度传感器的有效实现方案。     

基于自联想神经网络的发动机控制系统传感器故障诊断与重构

研究自联想神经网络及其在发动机控制系统传感器故障诊断及重构中的应用。自联想神经网络关键在于特征提取和噪声滤波。综合自联想网络的最优估计与故障诊断 ,自动区分估计误差和传感器故障。仿真结果表明这种方法不需要模型 ,能诊断传感器硬、软故障 ,当发动机性能蜕化时也能提供很好的解析余度。     

海上目标雷达与 AIS航迹时空匹配方法

针对海上目标的雷达与船舶自动识别系统(Automatic Identification System,AIS)中,航迹之间存在的时空不匹配现象,提出了在空间对准之后结合海上航迹运动特点,对 AIS航迹数据进行插值对准雷达目标航迹的方法,在解决雷达与 AIS航迹之间时空不匹配问题的同时,最大程度减小插值误差。该方法根据船舶航向变化率,结合航速航向法和内插外推法的优势,针对不同航迹特点自动选择最佳的插值配准方法,实现海上目标的雷达与 AIS航迹点的自动插值和时空对齐。仿真实验结果表明,所提方法针对海上目标复杂运动,可以自动匹配选择最佳插值方法,有效降低误差,实现雷达与 AIS航迹之间的时空匹配。     

空间遥感器中心筒式主支撑结构设计与仿真

针对某高分辨型光学成像载荷,从光学系统指标和结构稳定性要求出发,设计了一种具有加强结构的中心筒式主支撑结构。在空间遥感器的结构形式和光学系统指标要求的基础上,确定了给出了中心筒式主支撑结构的构型方案和材料。根据临界应力理论,计算并分析了结构的失稳强度。通过尺寸优化,保证了结构的基频和位置精度最优的同时相机得以大幅度减重。分析了中心筒式主支撑结构的静力学和动力学特性。有限元分析结果表明,结构满足光学系统公差,且具有足够的动刚度以对振动载荷抵抗性良好。     

电传飞机加速度传感器安装位置对飞行品质的影响

从飞行控制系统原理出发,以某型电传飞机为例,通过六自由度仿真对比,分析加速度传感器安装位置对飞行品质的影响,并从飞行品质的角度出发,对采用电传飞控系统飞机的加速度传感器安装位置提出建议.     

压力传感器单电源调理电路技术研究

对单电源供电的压力传感器调试中出现零位输出较大且存在相应死区的问题，进行了理论分析，找出了问题原因，采取了有效的解决措施，为传感器产品化和产业化奠定了基础。     

A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water-leaving radiance products obtained after calibration show a good consistency with in-situ and MODIS-Aqua observations, with errors less than the validated uncertainties of ±5% and ±35% endorsed for the remote-sensing measurements of water-leaving radiance and retrieval of chlorophyll concentrations respectively. The calibration results show a declining trend in detector sensitivity of the OCM-2 sensor, with a maximum effect in the shortwave spectrum, which provides evidence of sensor degradation and its profound effect on the striping artifacts in the OCM-2 data products.     

Crack monitoring method based on Cu coating sensor and electrical potential technique for metal structure

Advanced crack monitoring technique is the cornerstone of aircraft structural health monitoring.To achieve real-time crack monitoring of aircraft metal structures in the course of service,a new crack monitoring method is proposed based on Cu coating sensor and electrical potential difference principle.Firstly,insulation treatment process was used to prepare a dielectric layer on structural substrate,such as an anodizing layer on 2A12-T4 aluminum alloy substrate,and then a Cu coating crack monitoring sensor was deposited on the structure fatigue critical parts by pulsed bias arc ion plating technology.Secondly,the damage consistency of the Cu coating sensor and2A12-T4 aluminum alloy substrate was investigated by static tensile experiment and fatigue test.The results show that strain values of the coating sensor and the 2A12-T4 aluminum alloy substrate measured by strain gauges are highly coincident in static tensile experiment and the sensor has excellent fatigue damage consistency with the substrate.Thirdly,the fatigue performance discrepancy between samples with the coating sensor and original samples was investigated.The result shows that there is no obvious negative influence on the fatigue performance of the 2A12-T4 aluminum alloy after preparing the Cu coating sensor on its surface.Finally,crack monitoring experiment was carried out with the Cu coating sensor.The experimental results indicate that the sensor is sensitive to crack,and crack origination and propagation can be monitored effectively through analyzing the change of electrical potential values of the coating sensor.     

Design of on-board calibration methods for a digital sun sensor based on Levenberg–Marquardt algorithm and Kalman filters

Digital sun sensor is one of the most important sensors used in the Attitude Determination System (ADS) of the satellite. Due to the harsh environmental conditions that exist in the space, various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment. So, it is necessary to recalibrate the optical parameters of the aforementioned sensors. For this purpose, first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array, installation error, filter thickness and sensor misalignment. So, the mutual interfaces between the sensor parameters are considered in the developed model. In order to extract the sensor parameters, a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm. In addition, the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) have been utilized as sequential strategies. It will be shown that by considering a worst case of variation amount for sensor parameters, an accuracy improvement of about 17° is achieved by the developed calibration algorithms. Comparison between the developed algorithms represents that UKF has higher accuracy, shorter time convergence but higher computational load.