整合基于模型的系统工程与故障管理以实现自主航天任务

完全自主的航天任务（space mission）运行需要具备在无人干预的情况下检测并补偿故障的能力。为了应对这一挑战并为系统设计与运行提供基于模型的支持，将故障管理（FM）与基于模型的系统工程（MBSE）连接起来至关重要。这一方法已通过利用NASA的HelioSwarm任务早期设计信息，成功演示了基于模型的故障模式与影响分析及故障树的生成。

Fully autonomous space mission operations require the ability to detect faults and compensate for them without human intervention. To address this challenge and provide model-based support for system design and operations, it is important to connect fault management (FM) and model-based systems engineering (MBSE). This approach was successfully demonstrated with the model-based generation of a failure modes and effects analysis and fault trees using NASA’s HelioSwarm mission early design information.

随着NASA通过Artemis计划及该机构即将开展的深空空间科学（space science）任务不断拓展太空旅行的边界，提高系统自主性和韧性已不可避免地成为关键技术需求。自主运行需要故障管理（FM）软件来检测太空中出现的问题，以便在无人干预的情况下自动缓解这些问题。设计自主任务需要一种多学科方法，将FM与任务设计中使用的基于模型的系统工程（MBSE）方法连接起来，以确保在设计阶段就能构建、建模并集成具有韧性且容错的系统。

As NASA strives to push the boundaries of space travel with the Artemis program and the agency’s upcoming deep-space science missions, increased system autonomy and resiliency have inevitably become key technology needs. Autonomous operations require fault management (FM) software to detect issues that occur in space so they can be mitigated automatically without human intervention. Designing autonomous missions requires a multi-disciplinary approach that connects FM with the model-based systems engineering (MBSE) approach used in mission design to ensure that resilient, fault-tolerant systems are architected, modeled, and integrated during the design phase.

为了满足这一需求，NASA向Qualtech Systems Inc. (QSI) 授予了一份第二阶段小型企业创新研究（SBIR）合同，用于开发FM能力并增强其商业化工具集TEAMS®（该产品源于该公司早期NASA资助的SBIR工作的商业化），以支持HelioSwarm及其他NASA太阳物理任务。

To address this need, NASA awarded a Phase II Small Business Innovation Research (SBIR) contract to Qualtech Systems Inc. (QSI) for development of FM capabilities and enhancements to its commercially available toolset, TEAMS® (a product that resulted from commercialization of the company’s earlier NASA-sponsored SBIR work), to support HelioSwarm and other NASA heliophysics missions.

QSI的方法

The QSI Approach

这项工作中最重要的任务之一是将系统健康管理（SHM）和FM与系统工程（SE）流程连接起来。SHM/FM由一系列机制组成，通过防止故障发生，或在故障确实发生时进行检测并缓解，从而确保实现任务目标。SE流程负责协调、交叉检查并集成系统要素以实现任务目标，在系统的设计、规范以及验证与确认（V&V）过程中不可或缺。NASA经常为其SE流程采用基于模型的方法，并使用系统建模语言（SysML）作为框架。

One of the most important tasks in this effort was to connect system health management (SHM) and FM to the systems engineering (SE) process. Together, SHM/FM consists of a set of mechanisms that ensure that mission goals are achieved by preventing failures from occurring, or detecting and then mitigating them if they do occur. The SE process coordinates, cross-checks, and integrates system elements to achieve mission goals and is integral during the design, specification, and verification and validation (V&V) of systems. NASA often employs a model-based approach for its SE process, using Systems Modeling Language (SysML) as the framework.

尽管在实践中与SE有着内在的紧密联系，但SHM/FM实践通常并未与SE紧密集成。通常，SHM/FM仅在标称系统设计完成后才被纳入，这本质上使SHM/FM成为问题发生后的“创可贴”式修复，而没有考虑如何预防这些问题。此外，SE和SHM/FM通常涉及不同的学科专家组，且拥有各自孤立的知识库。这种情况可能导致使用不一致的建模方法和分析流程，并可能导致整个任务生命周期中的效率低下。

Despite their inherently close relationship to SE in practice, SHM/FM practices have typically not been tightly integrated with SE. Often, SHM/FM is incorporated only after a nominal system is designed, which essentially makes SHM/FM a bandage fix for problems after they occur, without considering how issues might have been prevented. In addition, SE and SHM/FM often involve separate sets of subject matter experts with stove-piped knowledge repositories. This situation can lead to use of modeling methodologies and analyses processes that yield inconsistent results, and can potentially result in inefficiencies throughout the mission life cycle.

这个由NASA资助的QSI团队的方法从项目开始就将SHM/FM直接集成到MBSE流程中。该方法通过展示SHM/FM方案如何缓解模拟的组件级物理和功能故障的影响，使得FM设计能够在运行环境中进行评估。该技术还促进了权衡研究，以在设计阶段评估各种FM架构的优劣。

This NASA-funded QSI team’s approach integrates SHM/FM directly within the MBSE process from the beginning of a project. This method enables the FM design to be evaluated in an operational context by showing how the SHM/FM schemes mitigate the effects of simulated component-level physical and functional failures. This technique also facilitates trade studies to evaluate the merits of various FM architectures during the design phase.

在此项SBIR工作中，QSI与SysML v2提交团队（SST）进行了合作——这是一个由终端用户、供应商、学术界人士和政府联络员组成的多元化小组，参与了SysML v2（SysML的最新迭代版本）规范的开发。QSI团队将FM概念和建模标准纳入了SysML v2，随后演示了SysML v2模型如何转换为由QSI工具集生成的故障空间模型。

Under this SBIR effort, QSI worked with the SysML v2 Submission Team (SST) — an assorted group of end users, vendors, academics, and government liaisons involved in the development of specifications for SysML v2, which is the latest iteration of SysML. The QSI team incorporated FM concepts and modeling standards into SysML v2, then they demonstrated how SysML v2 models could translate to the failure space models produced by the QSI toolset.

这一能力使系统工程师能够使用QSI的商业建模工具集，并分析SysML v2中捕获的系统设计的FM方面。通过捕获故障的原因和影响，QSI的工具集使任务设计师能够执行故障模式、影响及危害性分析（FMECAs）和故障树分析（FTAs），以分析、量化并改进系统的诊断能力和可用性。此外，该工具集还根据此类分析的结果推荐设计改进方案（例如，航天器上传感器的最佳位置），并以易于理解且可纳入设计的行业标准格式提供这些建议。

This capability enables systems engineers to use QSI’s commercial modeling tool set andanalyze the FM aspects of a system design captured in SysML v2. By capturing the causes and impacts of failures, QSI’s toolset enables mission designers to perform Fault Modes, Effects, and Criticality Analyses (FMECAs) and Fault Tree Analyses (FTAs) to analyze, quantify, and improve the diagnostics and availability of the system. Furthermore, the toolset recommends design improvements (e.g., optimal location of sensors onboard the spacecraft) based on the results from such analyses, and it provides these recommendations in industry-standard formats that can be easily understood and incorporated into the design.

在此次SBIR工作中，QSI工具集还进行了增强，以与MBSE框架对接，并促进任务设计中FM概念的创建、评估和选择。该工具集现在允许在设计过程的早期测试FM概念，从而将充分的检测和诊断能力构建到系统设计中，这可能降低总开发成本，促进任务团队成员之间的沟通与协调，并降低开发风险（成本和进度）。

During this SBIR effort, theQSI toolset was also enhanced to interface with an MBSE framework and facilitate the creation, evaluation, and selection of FM concepts for a mission design. The toolset now enables FM concepts to be tested early in the design process so that adequate detection and diagnosis can be built into the system design, which could potentially lower the total cost of development, facilitate enhanced communication and coordination among mission team members, and reduce development risks (cost and schedule).

HelioSwarm演示

The HelioSwarm Demonstration

HelioSwarm 将改变我们对太阳风（solar wind）中湍动以及日地系统（Sun–Earth system）关联的理解。该航天任务（space mission）使用一个由一个中心航天器和八个共轨（co-orbit）小卫星组成的星座（constellation），即“蜂群”，在动态的顺月空间环境（space environment）中首次对磁场（magnetic field）波动和质子流进行同步的多尺度测量。由于等离子体湍动（plasma turbulence）在从流体尺度运动到动力学尺度粒子动力学的多个尺度间进行能量转移（energy transfer），因此仅凭单一测量点或单一尺度的测量无法完全理解这一过程。HelioSwarm 的航天器将以数十至数千公里的间距飞行，使科学家能够重建湍动空间等离子体的三维结构和动力学。这些观测将揭示能量如何在太阳风中移动，从而改变我们对地球附近、太阳周围以及整个宇宙（universe）中运行的基本等离子体过程的理解。

HelioSwarm will transform our understanding of turbulence in the solar wind and the connected Sun–Earth system. The mission uses a constellation, or “swarm,” of one hub and eight co-orbiting small satellites to make the first simultaneous, multiscale measurements of magnetic-field fluctuations and proton flows in the dynamic cislunar space environment. Because plasma turbulence transfers energy across many scales, from fluid-scale motions to kinetic-scale particle dynamics, it cannot be fully understood from a single measurement point, or from measurements at only a single scale. HelioSwarm’s spacecraft will fly with separations ranging from tens to thousands of kilometers, allowing scientists to reconstruct the three-dimensional structure and dynamics of turbulent space plasma. These observations will reveal how energy moves through the solar wind, transforming our understanding of fundamental plasma processes that operate near Earth, around the Sun, and throughout the universe.

等离子体湍动是磁场波动和等离子体运动中所包含的能量从大空间尺度向小空间尺度级联的过程。当级联接近与动力学耗散相关的小空间尺度时，能量会转化为粒子热。如果没有空间等离子体中的湍动级联，宇宙的大部分区域将比观测到的温度低得多。由于它在包括空间等离子体在内的流体中发挥着基础性的热力学作用，许多人认为湍动流体是经典物理学中最重要且尚未解决的问题。

Plasma turbulence is the process by which energy contained in fluctuating magnetic fields and plasma motion cascades from large to smaller spatial scales. When the cascade approaches small spatial scales associated with kinetic dissipation, the energy transfers into particle heat. Without turbulent cascades in space plasmas, most of the universe would be far colder than observed. Because of the fundamental thermodynamic role it plays in fluids, including space plasmas, many contend that turbulent fluids are the most important unsolved problem in classical physics.

QSI 团队创建了 HelioSwarm 子系统和顶层任务需求的 SysML v2 设计模型，捕捉了从任务目标到设计的流程。随后，该团队使用其增强的工具集将 HelioSwarm SysML v2 模型转换为故障管理（FM）模型。HelioSwarm 模型由中心航天器和八个节点卫星的关键子系统组成，包括用于指令与数据处理（data handling）、电力、姿态控制（attitude control）、推进、热控、分离硬件载荷传感器以及地面与空间通信的子系统。利用 QSI 工具集，任务设计人员生成了故障模式、影响及危害性分析（FMECA）和故障树分析（FTA），并将其转换为标准化的 SysML 报告。此外，这些故障管理分析还生成了建议（例如针对传感器布局），作为系统设计的拟议更新提供。这一过程将支持具有固有冗余的小型航天器蜂群设计，以增强科学观测及美国国家航天局（NASA）的其他目标，例如为月面（lunar surface）作业提供任务支持。

The QSI team created a SysML v2 design model of HelioSwarm subsystems and top-level mission requirements, capturing the flowdown from mission goals to the design. The team then used its enhanced toolset to translate the HelioSwarm SysML v2 model into an FM model. The HelioSwarm models consist of key subsystems of the hub spacecraft and eight node satellites, including subsystems for command and data handling; electric power; attitude control; propulsion, thermal, and separation hardware payload sensors; and ground and space communications. Using the QSI toolset, mission designers then generated FMECAs and FTAs that were translated into a standardized SysML report. Furthermore, these FM analyses generated recommendations (e.g., for sensor placement) that were provided as proposed updates to the system design. This process will support the design of small spacecraft swarms with inherent redundancy to enhance science observations and other NASA goals, such as providing mission support for lunar surface operations.

与未来美国国家航天局任务及非美国国家航天局应用的相关性

Relevance to future NASA missions and non-NASA applications

通过这项最新的小企业创新研究（SBIR）工作开发的技术对于未来的美国国家航天局任务可能具有很高的价值，特别是那些需要自主运行的任务。QSI TEAMS® 工具集被选定为美国国家航天局 Gateway 项目的车辆系统管理功能基准，并保留了对未来载人航天器的适用性。系统设计工程师可以使用这项技术，在设计阶段之初就纳入故障缓解策略，通过对整体系统韧性的额外洞察来改进设计。

The technology developed via this latest SBIR effort could be of high value for future NASA missions — especially those that require autonomous operation. The QSI TEAMS® toolset was baselined for Vehicle Systems Management functions on NASA’s Gateway project and retains applicability to future human-rated spacecraft. System design engineers could use this technology to incorporate fault mitigation strategies to improve design with additional insight into the overall system resilience — right at the beginning of the design phase.

这项技术也可能在美国国家航天局之外有应用。全面且高效的故障管理分析和架构权衡研究对于复杂的、高价值的军事系统（如飞机、水面舰艇、潜艇，甚至现代地面作战车辆）至关重要。此外，这项技术还可能适用于新兴的商业航天系统、民用航空和海事系统、交通运输以及电力生产和分配设备。

This technology may also have applications outside of NASA. Comprehensive and efficient FM analyses and architecture trade studies are of critical importance to complex and high-value military systems such as aircraft, surface ships, submarines, and even modern ground-fighting vehicles. Additionally, this technology could be applicable to emerging commercial space systems, civilian aircraft and maritime systems, transportation, and power generation and distribution equipment.

有关此项工作的更多详细信息，请参阅相关的 TechPort 条目：此处、此处和此处。

For additional details about this effort, see the relevant TechPort entries: here, here, and here.

项目负责人：Dr. Sudipto Ghoshal, Mr. Deepak Haste, Qualtech Systems, Inc.

Project Lead(s): Dr. Sudipto Ghoshal, Mr. Deepak Haste, Qualtech Systems, Inc.

主办机构：美国国家航天局艾姆斯研究中心（Ames Research Center）

Sponsoring Organization(s): NASA Ames Research Center