John Ossenfort

Evaluation, Selection, and Application of Model-Based Diagnosis Tools and Approaches

Model-based approaches have proven fruitful in the design and implementation of intelligent systems that provide automated diagnostic functions. A wide variety of models are used in these approaches to represent the particular domain knowledge, including analytic state-based models, input-output transfer function models, fault propagation models, and qualitative and quantitative physics-based models. Diagnostic applications are built around three main steps: observation, comparison, and diagnosis. If the modeling begins in the early stages of system development, engineering models such as fault propagation models can be used for testability analysis to aid definition and evaluation of instrumentation suites for observation of system behavior. Analytical models can be used in the design of monitoring algorithms that process observations to provide information for the second step in the process, comparison of expected behavior of the system to actual measured behavior. In the final diagnostic step, reasoning about the results of the comparison can be performed in a variety of ways, such as dependency matrices, graph propagation, constraint propagation, and state estimation. Realistic empirical evaluation and comparison of these approaches is often hampered by a lack of standard data sets and suitable testbeds. In this paper we describe the Advanced Diagnostics and Prognostics Testbed (ADAPT) at NASA Ames Research Center. The purpose of the testbed is to measure, evaluate, and mature diagnostic and prognostic health management technologies. This paper describes the testbed’s hardware, software architecture, and concept of operations. A simulation testbed that

Wireless Space Plug-and-Play Architecture (SPA-Z)

Space Plug-and-Play Architecture (SPA), defined by the Air Force Research Laboratory, is a new standard for spacecraft component interconnections (AIAA-S-133-x-2013) providing new capability for managing intelligent components. Wireless Sensor Networks (WSN) based on the IEEE 802.15.4 Personal Area Network standard are finding increasing use in the home automation and emerging smart energy markets. The network protocol and application layers can be based on the ZigBee standard as defined by the ZigBee Alliance, providing a framework for component-based software that supports solutions from multiple vendors. SPA and ZigBee create selfconfiguring ad-hoc networks, but differ in their approach. SPA focuses on self-configuring components using wired interconnects while ZigBee forms self-configuring wireless networks. The optimal combination of SPA with ZigBee technology can bring the advantages of both methods to next-generation spacecraft by using self-configuring wireless networks for data and intelligent components with universal SPA-compliant interfaces. Mesh-enabled WSNs provide inherent fault tolerance and SPA provides dynamic fault management leading to low-power, low-cost ancillary sensing solutions for spacecraft. Self-configuring architectures are the key for supporting a large number of sensors in dynamic configurations, allowing intelligent response for fault tolerant networks. Plug-and-Play for sensor networks could be defined as the capability for application software to query any sensor module connected to the ad-hoc dynamic network using module resident information defining the sensors characteristics. The embedding of sensor information into each Wireless Sensor Module (WSM) allows identifying each sensor unambiguously and accurately in terms of function and status, without the use of any configuration database. The IEEE 1451 Smart Transducer Interface Standard defines Transducer Electronic Datasheets (TEDS) containing key information regarding sensor characteristics such as name, description, serial number and calibration information. SPA defines an extensible format called xTEDS using XML embedded meta-information for sensor management enabling software to identify the sensor and interpret the sensor data stream without reference to any external information. The application software is able to read the status of each sensor module, responding in real-time to changes of WSN configuration and provide the appropriate response for maintaining overall sensor system function, even when sensor modules fail or the network is reconfigured. Temporal integrity of sensor data delivery is ensured by the use of a global network clock and embedding timestamps into each measurement result accurate to one millisecond. SPA provides high-level mechanisms for self-configuration and integration with other spacecraft components and can significantly improve interoperability. The architecture and technical feasibility for creating wireless fault-tolerant sensor networks is presented through integration of SPA, IEEE 1451 and ZigBee into the proposed SPA-Z architecture. SPA provides the broad framework, the IEEE 1451 standards provide templates for TEDS and sensor management and ZigBee provides effective wireless network management. The approach is to tailor these multiple standards into a viable architecture. The result conforms to multiple standards, enables deterministic response and provides a capable publish/subscribe interface to application software. Our proposed software architecture for intelligent sensor management using the SPA standard will be discussed in the context of the specific tradeoffs required for effective use. Two examples are presented, the first highlights SPA-Z advantages for reconfigurable payloads and the second describes the development of a SPA compliant WSN.

A System for Fault Management and Fault Consequences Analysis for NASA's Deep Space Habitat

NASAs exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy

Intelligent Wireless Sensor Networks for Spacecraft Health Monitoring

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) Standard and the ZigBee 2007 Standard provide a framework for component-based software that supports interoperable solutions from multiple vendors. Mesh-enabled WSNs provide inherent fault tolerance and provide low-power, low-cost ancillary sensing systems for Integrated System Health Management for aerospace particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming self-managing dynamic sensor networks, allowing high-level application software to identify a module and interpret sensor values without using a pre-defined configuration database. Self-configuring system architectures for wireless sensor networks can support a large number of sensors in a dynamic configuration, providing intelligent response for fault tolerant networks. The IEEE 1451 Smart Transducer Interface Standard defines Transducer Electronic Datasheets (TEDS) containing key information regarding sensor characteristics such as name, description, serial number and calibration information. By locating this TEDS meta-information on the wireless sensor itself and enabling access to this information from the application software directly, the application can identify the sensor unambiguously and present the sensor data stream through network and module discovery. An interesting method for implementing the IEEE 1451 standard, based on the Air Force Research Lab’s Space Plug-and-Play Avionics (SPA) approach may simplify application software development compatible with modern software standards. The emerging AIAA SPA Standards can simplify adoption by standardizing application software interfaces and development by the use of the xTEDS based on Extensible Markup Language to provide sensor and actuator object virtualization within a standard framework. The authors propose an integration of ZigBee, IEEE 1451 and SPA to further define a facile software framework and the paper outlines the general architecture and approach for implementation of a prototype. The technical feasibility of creating fault-tolerant WSNs for Structural Health Monitoring is presented as a relevant example applied to composite structures for wind tunnel and flight tests to facilitate understanding key aspects of the aerospace vehicle design, test and operations life cycle.

Software architecture of sensor data distribution in planetary exploration

Data from mobile and stationary sensors will be vital in planetary surface exploration. The distribution and collection of sensor data in an ad-hoc wireless network presents unique challenges. Some of the conditions encountered in the field include: irregular terrain, mobile nodes, routing loops from clients associating with the wrong access point or repeater, network routing reconfigurations caused by moving repeaters, signal fade, and hardware failures. These conditions present the following problems: data errors, out of sequence packets, duplicate packets, and drop out periods (when the node is not connected). To mitigate the effects of these impairments, robust and reliable software architecture tolerant of communications outages must be implemented. This paper describes such a robust and reliable software infrastructure that meets the challenges of a distributed ad hoc network in a difficult environment and presents the results of actual field experiments testing the principles and exploring the underlying technology

Initial Demonstration of the Real-Time Safety Monitoring Framework for the National Airspace System Using Flight Data

As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have an automated framework to provide an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecast, predicted health of assets in the airspace, and so on. Towards this end, as part of our earlier work, we formulated the Real-Time Safety Monitoring (RTSM) framework for monitoring and predicting the state of safety and to predict unsafe events. In our previous work, the RTSM framework was demonstrated in simulation on three different constructed scenarios. In this paper, we further develop the framework and demonstrate it on real flight data from multiple data sources. Specifically, the flight data is obtained through the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Testbed that serves as a central point of collection, integration, and access of information from these different data sources. By testing and evaluating using real-world scenarios, we may accelerate the acceptance of the RTSM framework towards deployment. In this paper we demonstrate the frameworks capability to not only estimate the state of safety in the NAS, but predict the time and location of unsafe events such as a loss of separation between two aircraft, or an aircraft encountering convective weather. The experimental results highlight the capability of the approach, and the kind of information that can be provided to operators to improve their situational awareness in the context of safety.

Development and Testing of a Vehicle Management System for Autonomous Spacecraft Habitat Operations

As the increased distance between Earth-based mission control and the spacecraft results in increasing communication delays, small crews cannot take on all functions performed by ground today, and so vehicles must be more automated to reduce the crew workload for such missions. In addition, both near-term and future missions will feature significant periods when crew is not present, meaning the vehicles will need to operate themselves autonomously. NASA’s Advanced Exploration Systems Program pioneers new approaches for rapidly developing prototype systems, demonstrating key capabilities, and validating operational concepts for future humanmissions beyond low-Earth orbit. Under this program, NASA has developed and demonstrated multiple technologies to enable the autonomous operation of a dormant space habitat. These technologies included a fault-tolerant avionics architecture, novel spacecraft power system and power system controller, and autonomy software to control the habitat. The demonstration involved simulation of the habitat and multiple spacecraft sub-systems (power storage and distribution, avionics, and air-side life-support) during a multi-day test at NASA’s Johnson SpaceCenter. The foundation of the demonstrationwas ‘quiescent operations’ of a habitat during a 55 minute eclipse period. For this demonstration, the spacecraft power distribution system and air-side life support system were simulated at a high level of fidelity; additional systems were managed, but with lower fidelity operational constraints and system behavior. Operational constraints for real and simulated loads were developed by analyzing on-orbit hardware and evaluating future Exploration capable technology. A total of 13 real and simulated loads were used during the test. Eight scenarios including both nominal and offnominal conditions were performed. Over the course of the test, every application performed its desired functions successfully during the simulated tests. The results will inform both future tests, as well as provide insight to NASA’s domestic and international partners, as they

From Diagnosis to Action: An Automated Failure Advisor for Human Deep Space Missions

The major goal of current space system development at NASA is to enable human travel to deep space locations such as Mars and asteroids. At that distance, round trip communication with ground operators may take close to an hour, thus it becomes unfeasible to seek ground operator advice for problems that require immediate attention, either for crew safety or for activities that need to be performed at specific times for the attainment of scientific results. To achieve this goal, major reliance will need to be placed on automation systems capable of aiding the crew in detecting and diagnosing failures, assessing consequences of these failures, and providing guidance in repair activities that may be required. We report here on the most current step in the continuing development of such a system, and that is the addition of a Failure Response Advisor. In simple terms, we have a system in place the Advanced Caution and Warning System (ACAWS) to tell us what happened (failure diagnosis) and what happened because that happened (failure effects). The Failure Response Advisor will tell us what to do about it, how long until something must be done and why its important that something be done and will begin to approach the complex reasoning that is generally required for an optimal approach to automated system health management. This advice is based on the criticality and various timing elements, such as durations of activities and of component repairs, failure effects delay, and other factors. The failure advice is provided to operators (crew and mission controllers) together with the diagnostic and effects information. The operators also have the option to drill down for more information about the failure and the reasons for any suggested priorities.