CN109522944B - Multi-dimensional rapid classification method for faults of spacecraft - Google Patents
Multi-dimensional rapid classification method for faults of spacecraft Download PDFInfo
- Publication number
- CN109522944B CN109522944B CN201811279386.9A CN201811279386A CN109522944B CN 109522944 B CN109522944 B CN 109522944B CN 201811279386 A CN201811279386 A CN 201811279386A CN 109522944 B CN109522944 B CN 109522944B
- Authority
- CN
- China
- Prior art keywords
- fault
- faults
- aircraft
- classification
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000012545 processing Methods 0.000 claims abstract description 9
- 238000013467 fragmentation Methods 0.000 claims abstract description 7
- 238000006062 fragmentation reaction Methods 0.000 claims abstract description 7
- 238000002372 labelling Methods 0.000 claims abstract description 7
- 238000004891 communication Methods 0.000 claims description 12
- 238000013523 data management Methods 0.000 claims description 11
- 239000012634 fragment Substances 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 abstract description 6
- 238000005516 engineering process Methods 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 238000007599 discharging Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 230000001364 causal effect Effects 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000003449 preventive effect Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
Landscapes
- Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Navigation (AREA)
Abstract
Description
技术领域technical field
本发明涉及一种空间安全领域,特别是一种空间飞行器故障多维度快速分类方法。The invention relates to the field of space safety, in particular to a multi-dimensional rapid classification method for spacecraft faults.
背景技术Background technique
轨道救援系统针对受损卫星进行功能恢复救援。轨道救援系统具有广泛的军民两用潜力,处于国防军事与商业航天高度重叠的区域,是军民融合发展的重要支撑,在空间安全、在轨服务、商业救援与发射等方向具有重要的发展潜力和应用价值。The orbital rescue system performs function recovery rescue for damaged satellites. The Orbital Rescue System has a wide range of military-civilian dual-use potentials. It is located in an area where national defense, military and commercial aerospace highly overlap. It is an important support for the development of military-civilian integration. It has important development potential and Value.
世界主要航天强国针对快响应运载火箭和在轨服务技术均开展了相关研究,空间卫星救援等技术我国一直处于跟跑阶段,差距主要体现在起步晚、飞行验证少、技术成熟度不高,并未见关于空间故障飞行器的分类方法相关报道,空间故障飞行器分类方法的提出和应用对于未来空间飞行器的使用、救援以及空间资源的合理配置具有重要意义。The world's major aerospace powers have carried out relevant research on fast-response launch vehicles and on-orbit service technologies. my country has been in the follow-up stage in space satellite rescue and other technologies. The gap is mainly reflected in the late start, less flight verification, and low technology maturity. There is no report on the classification method of space faulty aircraft. The proposal and application of the classification method of space faulty aircraft is of great significance for the use, rescue and rational allocation of space resources of space vehicles in the future.
发明内容Contents of the invention
本发明的目的在于克服现有技术的上述不足,提供一种空间飞行器故障多维度快速分类方法,适用于未来多种航天器的故障快速分类分析,对研究未来的飞行器故障规律与救援模式有重要意义。The purpose of the present invention is to overcome the above-mentioned deficiencies of the prior art, to provide a multi-dimensional rapid classification method for spacecraft faults, which is applicable to the rapid classification and analysis of faults of various spacecraft in the future, and is important for studying future aircraft fault laws and rescue modes. significance.
本发明的上述目的是通过如下技术方案予以实现的:Above-mentioned purpose of the present invention is achieved by following technical scheme:
一种空间飞行器故障多维度快速分类方法,包括如下步骤:A multi-dimensional rapid classification method for spacecraft faults, comprising the following steps:
步骤一、建立故障分类的关键字检索目录;Step 1, establishing a keyword retrieval directory for fault classification;
步骤二、获取飞行器的故障信息;Step 2. Obtain the fault information of the aircraft;
步骤三、根据故障分类的关键字检索目录将飞行器的故障信息进行碎片化处理;Step 3, carry out fragmentation processing of the fault information of the aircraft according to the keyword retrieval directory of the fault classification;
步骤四、建立故障标签;Step 4, create a fault label;
步骤五、对步骤三中碎片化处理后的飞行器故障信息对应标签化处理;Step 5. Corresponding labeling processing of the aircraft fault information after fragmentation processing in step 3;
步骤六、建立飞行器故障标准库,将标签化处理后的飞行器故障信息存储在飞行器故障标准库中;Step 6, establish aircraft failure standard library, and store the aircraft failure information after tagging in the aircraft failure standard library;
步骤七、对飞行器故障进行分析时,从飞行器故障标准库进行关键字检索查询即可获得故障信息。Step 7. When analyzing aircraft faults, the fault information can be obtained by performing keyword search and query from the aircraft fault standard library.
在上述的一种空间飞行器故障多维度快速分类方法,所述步骤一中,所述故障分类关键字检索目录中故障类别包括控制系统故障、遥测控与通信系统故障、电源系统故障、动力系统故障、数据管理故障、热控系统故障和有效载荷故障。In the above-mentioned multi-dimensional rapid classification method for space vehicle faults, in the first step, the fault categories in the fault classification keyword retrieval catalog include control system faults, telemetry control and communication system faults, power supply system faults, and power system faults , data management failure, thermal control system failure and payload failure.
在上述的一种空间飞行器故障多维度快速分类方法,所述步骤一中,控制系统故障的关键字包括姿控故障、控制计算机、轨控故障、敏感器、导航和反作用轮;遥测控与通信系统故障的关键字包括遥测控、GPS、应答机和通信链路;电源系统故障的关键字包括电源调节器、电源供配电、电源充放电、电源控制器、蓄电池组、电源下位机和太阳电池阵;动力系统故障的关键字为动力执行机构;数据管理故障的关键字为数据管理存储器和数据处理器;热控系统故障的关键字为平台外部热控和单机热控;有效载荷故障的关键字为相机。In the above-mentioned method for multi-dimensional rapid classification of space vehicle failures, in the first step, the keywords of control system failures include attitude control failures, control computers, orbit control failures, sensors, navigation and reaction wheels; telemetry control and communication The keywords of system failure include telemetry and control, GPS, transponder and communication link; the keywords of power system failure include power regulator, power supply and distribution, power charging and discharging, power controller, battery pack, power lower computer and solar Battery array; keywords for power system failures are power actuators; keywords for data management failures are data management storage and data processors; keywords for thermal control system failures are platform external thermal control and stand-alone thermal control; payload failures are The keyword is camera.
在上述的一种空间飞行器故障多维度快速分类方法,所述步骤二中,飞行器故障信息的获取来源为外部地面测控站。In the above-mentioned multi-dimensional rapid classification method for spacecraft faults, in the second step, the acquisition source of aircraft fault information is an external ground measurement and control station.
在上述的一种空间飞行器故障多维度快速分类方法,所述飞行器的故障信息为所有故障类别信息无次序排列的综合文字。In the above-mentioned multi-dimensional rapid classification method for spacecraft faults, the fault information of the aircraft is a comprehensive text in which all fault category information is arranged out of sequence.
在上述的一种空间飞行器故障多维度快速分类方法,将飞行器的故障信息进行碎片化处理的具体方法为:In the above-mentioned multi-dimensional rapid classification method for spacecraft faults, the specific method for fragmenting the fault information of the aircraft is as follows:
S1:根据故障分类的关键字检索目录将飞行器的故障信息按照故障类别进行故障分类;S1: According to the keyword search directory of the fault classification, the fault information of the aircraft is classified according to the fault category;
S2:将相同故障类别的故障信息汇总,形成故障类别碎片;S2: Summarize the fault information of the same fault category to form fault category fragments;
S3:将故障类别碎片按照控制系统故障、遥测控与通信系统故障、电源系统故障、动力系统故障、数据管理故障、热控系统故障和有效载荷故障的顺序排序。S3: Sort the failure category fragments in the order of control system failure, telemetry control and communication system failure, power supply system failure, power system failure, data management failure, thermal control system failure and payload failure.
在上述的一种空间飞行器故障多维度快速分类方法,所述步骤四中,故障标签的类别和关键字与故障分类的关键字检索目录中的类别和关键字一致。In the above-mentioned multi-dimensional rapid classification method for spacecraft faults, in step 4, the categories and keywords of the fault label are consistent with the categories and keywords in the keyword retrieval directory for fault classification.
本发明与现有技术相比具有如下优点:Compared with the prior art, the present invention has the following advantages:
(1)本发明专门针对故障飞行器统计、分类困难的难题,建立空间飞行器故障数据库;该方法首先将空间飞行器故障模式进行分类,并将故障与卫星轨道高度、功能用途、平台类型、分系统组成等多维信息建立联系,解决飞行器历史故障数据量大、信息种类多、数据动态更新,对统计分析工作带来的困难;;(1) The present invention is specially aimed at the difficult difficult problem of fault aircraft statistics and classification, and establishes a space aircraft fault database; the method first classifies the space aircraft fault modes, and forms faults with satellite orbit height, functional use, platform type, and sub-systems Establish links with multi-dimensional information such as aircraft, and solve the difficulties brought about by the large amount of aircraft historical fault data, various types of information, and dynamic data updates, which have brought about statistical analysis;
(2)本发明专门针对故障飞行器统计、分类困难的难题,提出了一种可用于空间飞行器故障大数据快速分析的多维度分类方法,运用卫星故障数据库作为算法的训练样本,形成可以分析异常参数的故障分类网络结构,用于空间飞行器故障数据的快速统计分析;(2) The present invention is specifically aimed at the difficult problem of statistics and classification of faulty aircraft, and proposes a multi-dimensional classification method that can be used for rapid analysis of large data of space vehicle faults, and uses the satellite fault database as the training sample of the algorithm to form abnormal parameters that can be analyzed The fault classification network structure is used for fast statistical analysis of space vehicle fault data;
(3)本发明随着数据库的扩展可以进一步升级,适应新型飞行器故障类型,也可以提高故障分类准确率,后续可以为故障快速分析与分类、产品质量提升等工作提供数据支撑。(3) With the expansion of the database, the present invention can be further upgraded to adapt to new types of aircraft faults, and can also improve the accuracy of fault classification, and can provide data support for rapid fault analysis and classification, product quality improvement and other work.
附图说明Description of drawings
图1为本发明快速分类方法流程图;Fig. 1 is the flow chart of rapid classification method of the present invention;
图2为本发明故障分类关键字检索目录示意图。Fig. 2 is a schematic diagram of the retrieval directory of fault classification keywords in the present invention.
具体实施方式detailed description
下面结合附图和具体实施例对本发明作进一步详细的描述:Below in conjunction with accompanying drawing and specific embodiment the present invention will be described in further detail:
本发明克服现有科研成果的不足,统计历史上空间飞行器的已记载故障,建成数据库并完成合理的标签化快速分类方法研究,提出未来可快速分析、判断空间飞行器故障的方法。The present invention overcomes the shortcomings of existing scientific research achievements, counts the recorded faults of space vehicles in history, builds a database and completes the research on reasonable labeling and rapid classification methods, and proposes a method for quickly analyzing and judging space vehicle failures in the future.
如图1所示为快速分类方法流程图,由图可知,一种空间飞行器故障多维度快速分类方法,包括如下步骤:As shown in Figure 1, it is a flow chart of the rapid classification method. It can be seen from the figure that a multi-dimensional rapid classification method for spacecraft faults includes the following steps:
步骤一、建立故障分类的关键字检索目录;故障分类关键字检索目录中故障类别包括控制系统故障、遥测控与通信系统故障、电源系统故障、动力系统故障、数据管理故障、热控系统故障和有效载荷故障。控制系统故障的关键字包括姿控故障、控制计算机、轨控故障、敏感器、导航和反作用轮;遥测控与通信系统故障的关键字包括遥测控、GPS、应答机和通信链路;电源系统故障的关键字包括电源调节器、电源供配电、电源充放电、电源控制器、蓄电池组、电源下位机和太阳电池阵;动力系统故障的关键字为动力执行机构;数据管理故障的关键字为数据管理存储器和数据处理器;热控系统故障的关键字为平台外部热控和单机热控;有效载荷故障的关键字为相机。Step 1. Establish a keyword retrieval directory for fault classification; the fault categories in the fault classification keyword retrieval directory include control system faults, telemetry control and communication system faults, power system faults, power system faults, data management faults, thermal control system faults and Payload failure. The keywords of control system failure include attitude control failure, control computer, orbit control failure, sensor, navigation and reaction wheel; the keywords of telemetry control and communication system failure include telemetry control, GPS, transponder and communication link; power system The keywords of failure include power conditioner, power supply and distribution, power charging and discharging, power controller, battery pack, power lower computer and solar array; the keyword of power system failure is power actuator; the keyword of data management failure The memory and data processor are managed for data; the keywords of thermal control system failure are platform external thermal control and stand-alone thermal control; the keywords of payload failure are camera.
步骤二、获取飞行器的故障信息;获取来源为外部地面测控站;飞行器的故障信息为所有故障类别信息无次序排列的综合文字。对于过去10多年的几千个飞行器故障(含卫星、飞船)进行了统计,故障系统包括遥测控系统、控制系统、电源系统、动力系统等,获取当前技术条件下较全面的空间飞行器故障信息。Step 2. Obtain the fault information of the aircraft; the source of the acquisition is an external ground measurement and control station; the fault information of the aircraft is a comprehensive text of all fault category information arranged in no order. Statistics have been made on thousands of aircraft failures (including satellites and spacecraft) in the past 10 years. The failure systems include telemetry and control systems, control systems, power systems, power systems, etc., to obtain more comprehensive space vehicle failure information under current technical conditions.
步骤三、根据故障分类的关键字检索目录将飞行器的故障信息进行碎片化处理;将飞行器的故障信息进行碎片化处理的具体方法为:Step 3. According to the keyword search directory of the fault classification, the fault information of the aircraft is fragmented; the specific method of fragmenting the fault information of the aircraft is as follows:
S1:根据故障分类的关键字检索目录将飞行器的故障信息按照故障类别进行故障分类;S1: According to the keyword search directory of the fault classification, the fault information of the aircraft is classified according to the fault category;
S2:将相同故障类别的故障信息汇总,形成故障类别碎片;S2: Summarize the fault information of the same fault category to form fault category fragments;
S3:将故障类别碎片按照控制系统故障、遥测控与通信系统故障、电源系统故障、动力系统故障、数据管理故障、热控系统故障和有效载荷故障的顺序排序。S3: Sort the failure category fragments in the order of control system failure, telemetry control and communication system failure, power supply system failure, power system failure, data management failure, thermal control system failure and payload failure.
步骤四、建立故障标签;故障标签的类别和关键字与故障分类的关键字检索目录中的类别和关键字一致。Step 4: Create a fault label; the categories and keywords of the fault label are consistent with the categories and keywords in the keyword retrieval directory for fault classification.
步骤五、对步骤三中碎片化处理后的飞行器故障信息对应标签化处理;Step 5. Corresponding labeling processing of the aircraft fault information after fragmentation processing in step 3;
步骤六、建立飞行器故障标准库,将标签化处理后的飞行器故障信息存储在飞行器故障标准库中;Step 6, establish aircraft failure standard library, and store the aircraft failure information after tagging in the aircraft failure standard library;
步骤七、对需要飞行器的故障进行分析研究室时,按类或按关键字从飞行器故障标准库进行关键字检索查询即可获得故障信息。统计和分析航天器在轨实际发生的故障,可以从中发现在轨故障发生的规律,并指导航天器采取预防或纠正措施。文章在收集航天器在轨故障的基础上,划分了故障的类别,总结了故障发生趋势。Step 7. When analyzing and researching the faults of the aircraft, the fault information can be obtained by performing keyword search and query from the aircraft fault standard database by category or keyword. Statistical and analysis of the actual failures of the spacecraft on-orbit can reveal the law of on-orbit failures and guide the spacecraft to take preventive or corrective measures. Based on the collection of on-orbit failures of spacecraft, the article divides the categories of failures and summarizes the trend of failures.
并且随着数据库的扩展可以进一步升级,适应新型飞行器故障类型,也可以提高故障分类准确率,后续可以为故障快速分析与分类、产品质量提升等工作提供数据支撑。通过建立飞行器故障数据库,分析得到故障影响因果知识,可以对未来空间飞行器的参数异常及异常现象可能导致的故障进行统计分析。And with the expansion of the database, it can be further upgraded to adapt to new types of aircraft faults, and can also improve the accuracy of fault classification. In the future, it can provide data support for rapid fault analysis and classification, product quality improvement and other work. By establishing the aircraft fault database and analyzing the cause and effect knowledge of the fault, it is possible to statistically analyze the faults that may be caused by the abnormal parameters of the future spacecraft and the abnormal phenomena.
设计空间飞行器故障多维度快速分类标签网络结构,提炼形成一种空间飞行器故障系统快速分类工具,可以通过输入故障情况,依据已经研究的数据库、科学因果知识和整体影响系数经验知识,可快速形成对故障情况的判断。Design a multi-dimensional rapid classification label network structure for spacecraft faults, and refine it to form a rapid classification tool for spacecraft fault systems. By inputting fault conditions, based on the researched database, scientific causal knowledge, and empirical knowledge of the overall impact coefficient, it can quickly form a pair of faults. Judgment of fault conditions.
本发明说明书中未作详细描述的内容属本领域技术人员的公知技术。The content that is not described in detail in the description of the present invention belongs to the well-known technology of those skilled in the art.
Claims (3)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811279386.9A CN109522944B (en) | 2018-10-30 | 2018-10-30 | Multi-dimensional rapid classification method for faults of spacecraft |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811279386.9A CN109522944B (en) | 2018-10-30 | 2018-10-30 | Multi-dimensional rapid classification method for faults of spacecraft |
Publications (2)
Publication Number | Publication Date |
---|---|
CN109522944A CN109522944A (en) | 2019-03-26 |
CN109522944B true CN109522944B (en) | 2022-12-13 |
Family
ID=65772692
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811279386.9A Active CN109522944B (en) | 2018-10-30 | 2018-10-30 | Multi-dimensional rapid classification method for faults of spacecraft |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109522944B (en) |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1884852B1 (en) * | 2006-08-04 | 2009-08-05 | Honeywell Inc. | Tuning procedure for aircraft fault detection |
CN103455036A (en) * | 2012-06-05 | 2013-12-18 | 国家电网公司 | Scene aerial patrol method and aircraft |
CN105183937A (en) * | 2015-07-17 | 2015-12-23 | 中国运载火箭技术研究院 | Fault diagnosis method suitable for electrical system of unmanned aerial vehicle |
CN105223843A (en) * | 2015-09-14 | 2016-01-06 | 中国运载火箭技术研究院 | A kind of re-entry space vehicle combination property verification system based on data sharing |
CN106959911A (en) * | 2017-02-24 | 2017-07-18 | 上海与德信息技术有限公司 | The automatic generation method and device of terminal equipment failure |
CN108100292A (en) * | 2016-11-24 | 2018-06-01 | 中航贵州飞机有限责任公司 | A kind of method that airplane fault is excluded based on big data |
CN108416061A (en) * | 2018-03-26 | 2018-08-17 | 福州大学 | The foundation of unmanned plane Image Database, classification and the search method of suitable power inspection |
CN108647008A (en) * | 2018-04-27 | 2018-10-12 | 北京航空航天大学 | Move the digital satellite power subsystem source code artificial intelligence Writing method of coupling |
-
2018
- 2018-10-30 CN CN201811279386.9A patent/CN109522944B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1884852B1 (en) * | 2006-08-04 | 2009-08-05 | Honeywell Inc. | Tuning procedure for aircraft fault detection |
CN103455036A (en) * | 2012-06-05 | 2013-12-18 | 国家电网公司 | Scene aerial patrol method and aircraft |
CN105183937A (en) * | 2015-07-17 | 2015-12-23 | 中国运载火箭技术研究院 | Fault diagnosis method suitable for electrical system of unmanned aerial vehicle |
CN105223843A (en) * | 2015-09-14 | 2016-01-06 | 中国运载火箭技术研究院 | A kind of re-entry space vehicle combination property verification system based on data sharing |
CN108100292A (en) * | 2016-11-24 | 2018-06-01 | 中航贵州飞机有限责任公司 | A kind of method that airplane fault is excluded based on big data |
CN106959911A (en) * | 2017-02-24 | 2017-07-18 | 上海与德信息技术有限公司 | The automatic generation method and device of terminal equipment failure |
CN108416061A (en) * | 2018-03-26 | 2018-08-17 | 福州大学 | The foundation of unmanned plane Image Database, classification and the search method of suitable power inspection |
CN108647008A (en) * | 2018-04-27 | 2018-10-12 | 北京航空航天大学 | Move the digital satellite power subsystem source code artificial intelligence Writing method of coupling |
Non-Patent Citations (1)
Title |
---|
空间飞行器故障诊断技术的特点;荣吉利等;《哈尔滨工业大学学报》;19951030;142-146页 * |
Also Published As
Publication number | Publication date |
---|---|
CN109522944A (en) | 2019-03-26 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Pierdicca et al. | Deep convolutional neural network for automatic detection of damaged photovoltaic cells | |
CN106712713B (en) | The monitoring system and monitoring and abnormal localization method of a kind of photovoltaic plant | |
WO2022174679A1 (en) | Method and apparatus for predicting voltage inconsistency fault of battery cells, and server | |
US11270528B2 (en) | Apparatus and method for vehicle maintenance scheduling and fault monitoring | |
CN116542651A (en) | On-orbit autonomous health management system and method for payload of spacecraft | |
CN105306526B (en) | A kind of thrust-augmented rocket big flow telemetry data reduction processing method | |
CN106650963A (en) | Electric car charging equipment detection and maintenance managing method and device | |
CN105488539A (en) | Generation method and device of classification method, and estimation method and device of system capacity | |
CN106598033A (en) | PHM (Prognostic and Health Management) system for unmanned aerial vehicle based on middleware | |
CN113673171B (en) | Docking mechanism digital twin test system based on historical data driving and machine learning and operation method thereof | |
CN109522944B (en) | Multi-dimensional rapid classification method for faults of spacecraft | |
CN105373620A (en) | Mass battery data exception detection method and system for large-scale battery energy storage power stations | |
CN102789235B (en) | Method for determining reconfigurability of satellite control system | |
Xing et al. | Deciphering the enigma of satellite computing with cots devices: Measurement and analysis | |
Grantham Lough et al. | Function based risk assessment: mapping function to likelihood | |
CN106774411A (en) | Unmanned plane middleware system based on PHM | |
CN107330638B (en) | Aerospace project risk comprehensive evaluation method oriented to decision support | |
CN109409000B (en) | Test coverage analysis method | |
Bernal-Mencia et al. | Machine learning for early satellite anomaly detection | |
Raigoza et al. | Electric vertical take-off and landing (eVTOL) vehicle reliability and safety analysis | |
CN115757427A (en) | Storage method and software for spacecraft test data | |
CN110428516B (en) | GJB289A bus data recording and processing method | |
Pollet et al. | Environmental life cycle assessments for the design exploration of electric uavs | |
Wenting et al. | Preliminary idea of rocket fault diagnose driven by digital twin | |
CN112541629A (en) | Prediction method, system, electronic device and storage medium for airport selection |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |