环境减灾卫星高光谱数据在减灾中的应用研究

利用中国环境减灾-1A（HJ-1A）卫星高光谱数据开展减灾应用研究,可提高灾害预警监测能力,提高灾害预警监测精度,拓展国产星载高光谱数据应用的广度和深度。文章简要介绍了HJ-1A高光谱数据的主要特征,阐述了高光谱灾害监测的原理,初步开展了该数据在减灾领域中的应用研究,并展望了HJ-1A高光谱数据在区域土壤有机碳估算等其...     

基于Pushlet架构的航天器在轨实时监测报警系统

基于Pushlet架构,设计了一个浏览器／服务器（B／S）模式的航天器在轨实时监测报警系统。该系统采用“发布／订阅”机制,客户端需要首先订阅在服务器端的某个主题,服务器端则接收订阅并进行注册,同时实时接收航天器在轨遥测数据并进行判读,通过持久HTTP连接向监测客户端实时推送异常判读结果,实现航天器在轨运行状态的实时监测和报警功能。测试结果表明,文章提出的系统具有实时性强、效率高和稳定性好的优点。     

基于大数据分析方法的商用飞机MOC9试验项目管理可视化模型研究

实践表明,大数据技术可以对管理过程赋能,商用飞机MOC9 试验项目作为商用飞机研制复杂高端项目群中的重要项目,其在研制期间会产生大量项目管理数据,因此,研究如何利用大数据技术推动该类项目实现项目目标十分必要。基于商用飞机研制项目群下MOC9 试验项目的特点及其对大数据管理的需求,结合大数据技术处理流程和方法对MOC9 试验项目从架构策划、数据获取与存储、数据清洗处理、分析挖掘、可视化展示多方面开展研究。结果表明：通过大数据技术对MOC9 试验项目建立量化的可视化模型,对项目经理掌握项目整体情况、定位问题根本原因、识别项目潜在风险非常有帮助。     

基于健康监测的飞机结构寿命预测技术

飞机结构健康监测技术在飞机的结构设计、飞行及维护过程中发挥着重要作用,该技术可用于结构健康状况预判、辅助维修与维护决策。本文首先介绍了当前结构健康监测的概念及其适用范围,讨论了结构健康监测相关规范要求,以F-35 和A400M 为例分析了国外飞机结构健康监测技术的典型工程案例,并给出了典型飞机单机跟踪和寿命控制、某老龄飞机载荷谱实测及寿命预测,讨论了基于裂纹的监测方法研究及限制其应用的主要因素。在此基础上,提出了飞机结构健康监测系统设计的主要思路,给出了寿命预计的基本流程,阐述了其中控制点选择、飞参筛选、载荷/应变方程构建、损伤计算及寿命评估、结果输出及方程验证等主要环节。最后,对航空领域未来开展结构健康监测智能化研究进行了展望。     

载人航天器防火安全设计

防火安全是载人航天器总体设计所关注的重点项目之一。文章按照火灾发生三要素,结合以往密封舱防火安全设计经验,从密封舱内可燃物控制、舱内氧浓度控制、防止点火源形成、防止火灾传播、密封舱烟火监测和密封舱灭火6个方面对载人航天器防火安全设计方法进行了归纳总结。该研究可为我国后续载人航天器密封舱防火设计提供重要依据,确保载人航天器任务期间的安全可靠性。     

电子束熔丝增材制造过程随动测温阵列系统

实时监测电子束熔丝增材制造过程的温度场分布对于抑制变形、提高电子束熔丝增材制造质量具有重要意义.研制了一套电子束熔丝增材制造过程的随行动态测温阵列系统,对整个装置进行了系统设计、硬件集成、软件编写和试验验证.结果表明,该随动测温阵列系统在电子束熔丝增材制造过程的高真空、高温、高辐射、高金属蒸气等恶劣环境中能稳定工作,不...     

Correlation-weighted least squares residual algorithm for RAIM

The Least Squares Residual (LSR) algorithm, one of the classical Receiver Autonomous Integrity Monitoring (RAIM) algorithms for Global Navigation Satellite System (GNSS), presents a high Missed Detection Risk (MDR) for a large-slope faulty satellite and a high False Alarm Risk (FAR) for a small-slope faulty satellite. From the theoretical analysis of the high MDR and FAR cause, the optimal slope is determined, and thereby the optimal test statistic for fault detection is conceived, which can minimize the FAR with the MDR not exceeding its allowable value. To construct a test statistic approximate to the optimal one, the Correlation-Weighted LSR (CW-LSR) algorithm is proposed. The CW-LSR test statistic remains the sum of pseudorange residual squares, but the square for the most potentially faulty satellite, judged by correlation analysis between the pseudorange residual and observation error, is weighted with an optimal-slope-based factor. It does not obey the same distribution but has the same non-central parameter with the optimal test statistic. The superior performance of the CW-LSR algorithm is verified via simulation, both reducing the FAR for a small-slope faulty satellite with the MDR not exceeding its allowable value and reducing the MDR for a large-slope faulty satellite at the expense of FAR addition.     

Deformation monitoring using GNSS-R technology

GNSS reflectometry (GNSS-R) has been widely studied in recent years for various applications, such as soil moisture monitoring, biomass analysis, and sea state monitoring. This paper presents the concept of a novel application of using GNSS-R technology for deformation monitoring. Instead of installing GNSS on the deformation body to sense the movement, GNSS-R deformation monitoring system estimates the deformation from receiving GNSS signal reflected by the deformation body remotely. A prototype of GNSS-R deformation monitoring system has been developed based on GNSS software receiver technology. A 3D geometrical model of GNSS signal reflection has been used to reveal the relationship between the change of carrier phase difference and deformation. After compensating the propagation path delay changes caused by satellite movement, the changes in the remaining carrier phase difference are linked to the deformation. Field tests have been carried using the GNSS-R system developed and the results show sub-centimeter level deformation can be observed with the new technology. Unlike other GNSS deformation monitoring methods, GNSS-R receivers are not installed on the slope which makes this new technology more attractive.     

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.     

A pre-generated matrix-based method for real-time robotic drilling chatter monitoring

Currently, due to the detrimental effects on surface finish and machining system, chatter has been one crucial factor restricting robotic drilling operations, which improve both quality and efficiency of aviation manufacturing. Based on the matrix notch filter and fast wavelet packet decomposition, this paper presents a novel pre-generated matrix-based real-time chatter monitoring method for robotic drilling. Taking vibration characteristics of robotic drilling into account, the matrix notch filter is designed to eliminate the interference of spindle-related components on the measured vibration signal. Then, the fast wavelet packet decomposition is presented to decompose the filtered signal into several equidistant frequency bands, and the energy of each sub-band is obtained. Finally, the energy entropy which characterizes inhomogeneity of energy distribution is utilized as the feature to recognize chatter on-line, and the effectiveness of the presented algorithm is validated by extensive experimental data. The results show that the proposed algorithm can effectively detect chatter before it is fully developed. Moreover, since both filtering and decomposition of signal are implemented by the pre-generated matrices, calculation for an energy entropy of vibration signal with 512 samples takes only about 0.690 ms. Consequently, the proposed method achieves real-time chatter monitoring for robotic drilling, which is essential for subsequent chatter suppression.