Data reduction and correction algorithm for digital real-time processing of cosmic ray measurements: NM64 monitoring at Dourbes

We present a data correction algorithm for real-time data processing for the NM64 galactic cosmic ray neutron monitor at the Royal Meteorological Institute (RMI) in Dourbes, Belgium. The correction is based on three main tests: a continuity test, tube ratios test and a derivative test. The continuity test works as a high pass filter with a threshold based on the entire recorded dataset. Additionally, it monitors whether the logging takes place at regular intervals (continuously). The ratios test identifies noisy sections and the final derivative test criterion will identify single or double spikes by testing them against the median increase of the intensities. Using these criteria, all data from the cosmic ray station at Dourbes is corrected in real time. Test results have been compared with data from verified neutron monitor stations with a similar geomagnetic cutoff rigidity.     

基于一致性融合和神经网络的航空发动机气路系统故障诊断方法

以信息融合为基础,运用GRNN神经网络对航空发动机气路系统进行故障诊断,提出了一种基于一致性融合和神经网络相结合的故障诊断方法。试验结果表明,该方法能快速识别航空发动机气路系统故障,并且对其他机械设备的故障诊断具有一定的参考价值。     

基于CCSDS标准的航天器上行遥控链路 协议体系与可靠性技术

针对航天测控领域中上行遥控业务的协议体系选择与可靠性设计问题,在对我国现行国军标技术指标要求与现有航天测控系统天地基遥控技术特点进行归纳梳理的基础上,基于空间段信息传输无线链路特点与CCSDS(Consultative Committee for Space Data Systems,空间数据系统咨询委员会)标准规范,研究给出了适用于我国航天测控任务的空间段遥控协议体系与可靠性措施,利用梳理统计方法对上行遥控体制进行了数学建模分析,并与CCSDS给出的应用算例进行了对比分析.分析结果表明,所涉及的上行遥控体制与CCSDS标准规范的工作效能基本相当,能够满足我国航天任务上行遥控任务使用需求.     

Nonlinear dynamic modeling of a helicopter planetary gear train for carrier plate crack fault diagnosis

Planetary gear train plays a significant role in a helicopter operation and its health is of great importance for the flight safety of the helicopter. This paper investigates the effects of a planet carrier plate crack on the dynamic characteristics of a planetary gear train, and thus finds an effec-tive method to diagnose crack fault. A dynamic model is developed to analyze the torsional vibra-tion of a planetary gear train with a cracked planet carrier plate. The model takes into consideration nonlinear factors such as the time-varying meshing stiffness, gear backlash and viscous damping. Investigation of the deformation of the cracked carrier plate under static stress is performed in order to simulate the dynamic effects of the planet carrier crack on the angular displacement of car-rier posts. Validation shows good accuracy of the developed dynamic model in predicting dynamic characteristics of a planetary gear train. Fault features extracted from predictions of the model reveal the correspondence between vibration characteristic and the conditions (length and position) of a planet carrier crack clearly.     

Simultaneous state and actuator fault estimation for satellite attitude control systems

In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The simulation results show satisfactory perfor-mance in estimating states and actuator faults. It also shows that multiple faults can be estimated successfully.     

基于综合模糊聚类算法的液体火箭发动机故障诊断

基于液体火箭发动机正常及故障状况数据的完备程度和数据质量的不断提高,提出一种基于数据驱动的综合模糊聚类算法用于故障诊断。采用模糊c均值(FCM)算法对已知正常样本数据进行聚类得到最优的聚类中心,将所得到的聚类中心作为先验样本数据用于传递闭包法最优分类结果的选择从而得到故障检测结果,该算法只需要少量的正常先验样本数据就能快速、准确的检测出故障;随后采用FCM算法进行故障分类,可以根据现有的故障数据库进行聚类得到对应的故障类型,并且可以给出故障幅值范围。模型仿真结果表明:该算法对故障的检测率可达968%,故障隔离率达到94%。某型液体火箭发动机实际试车数据结果表明:该故障诊断算法能够准确及时的检测并隔离出故障。     

小波变换在遥测数据处理中的应用

采用离散小波变换方法对在轨卫星遥测数据进行处理,利用噪声和信号在不同小波尺度上的性质不同．基于极大极小化思想选取去噪处理中的阈值,达到分离噪声和信号的目的。结果表明：利用小波变换可有效消除卫星遥测数据的噪声。     

基于自适应遗传BP算法神经网络数据融合的空中目标识别

空中目标识别是现代防空作战的重要研究内容。本文利用不同类型目标产生的多类型传感器的数据信息对目标进行识别。为了训练神经网络目标识别分类器,将遗传算法和BP算法相结合,提出了一种新的自适应遗传BP算法,利用这种神经网络来确定指标的权值。仿真试验结果表明,基于自适应遗传BP算法神经网络的识别是一种简单、可靠的目标识别方法,具有很好的目标识别效果。     

飞机电源系统故障诊断方法综述及发展趋势

飞机电源系统是机上一切用电设备的电能来源,其安全性与可靠性至关重要。在环保和高效发展需求的背景下,现代航空工业正在推进以电能为核心的多电/全电飞机技术的研究和应用。电驱动装置和电力电子器件的广泛使用导致飞机电源系统结构的复杂化,对飞机的可靠性、安全性、测试性和维修性提出了更高的要求,研究飞机电源系统的故障诊断技术具有重要意义。首先介绍了飞机电源系统的组成结构和各自功能,概述了飞机电源系统的发展历程,对比了国内外典型电源系统的特征,总结了飞机电源系统中的主要故障模式、故障特点和失效原因,并提出了一种飞机电源健康管理系统的设计架构,然后综述了国内外基于模型和基于数据的故障诊断方法研究进展,从准确度、数据需求量、适用性和实现难易程度等方面评述了各类诊断方法的特点,最后指出了飞机电源系统故障诊断技术面临的挑战和发展趋势。