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Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by.
Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by. In addition, to make the monitoring process efficient, and to avoid the potential for information overload on human operators, attention focusing must also be addressed. When an anomaly occurs, more often than not several sensors are affected, and the partially redundant information they provide can be confusing, particularly in a crisis situation where a response is needed quickly.
The integration of new capabilities into the Mission Control Center at the Johnson Space Center in Houston, Texas in order to improve the data monitoring and analysis of the STS is discussed. User interface application software and systems, such as the flight data file Shuttle mission simulator and failure analysis program, to be utilized for flight operations automation are examined. Consideration is given to task automation, the trend monitoring system, the data retrieval system, and the launch processing system. The development and functions of the Shuttle data analysis system, which is to operate in real time, are described.
During early manned spacecraft operations, the primary role of ground telemetry systems was data display to flight controllers. As manned spaceflights have increased in complexity, greater demands have been placed on flight controllers to simultaneously monitor systems and replan systems operations. This has led to interest in automated telemetry monitoring systems to decrease the workload on flight controllers. The Mission Operations Directorate at the Lyndon B. Johnson Space Center has developed a five layer model to integrate various monitoring and analysis technologies such as digital filtering, fault detection algorithms, and expert systems. The paper describes the five layer model and explains how it has been used to guide prototyping efforts at Mission Control. Results from some initial expert systems are presented. The paper also describes the integrated prototype currently under development which implements a real time expert system to assist flight controllers in the Mission Control Center in monitoring Space Shuttle communications systems.
Since the launch of NASA's Extreme Ultraviolet Explorer (EUVE) satellite in 1992, there has only been a handful of occurrences that have warranted manual intervention in the EUVE Science Operations Center (ESOC). So, in an effort to reduce costs, the current environment is being redesigned to utilize a combination of off-the-shelf packages and recently developed artificial intelligence (AI) software to automate the monitoring of the science payload and ground systems. The successful implementation of systemic automation would allow the ESOC to evolve from a seven day/week, three shift operation, to a seven day/week one shift operation. First, it was necessary to identify all areas considered mission critical. These were defined as follows: (1) The telemetry stream must be monitored autonomously and anomalies identified. (2) Duty personnel must be automatically paged and informed of the occurrence of an anomaly. (3) The 'basic' state of the ground system must be assessed. (4) Monitors should check that the systems and processes needed to continue in a 'healthy' operational mode are working at all times. (5) Network loads should be monitored to ensure that they stay within established limits. (6) Connectivity to Goddard Space Flight Center (GSFC) systems should be monitored as well, not just for connectivity of the network itself but also for the ability to transfer files. (7) All necessary peripheral devices should be monitored. This would include the disks, routers, tape drives, printers, tape carousel, and power supplies. (8) System daemons such as the archival daemon, the Sybase server, the payload monitoring software, and any other necessary processes should be monitored to ensure that they are operational. (9) The monitoring system needs to be redundant so that the failure of a single machine will not paralyze the monitors. (10) Notification should be done by means of looking though a table of the pager numbers for current 'on call' personnel. The software should be capable of dialing out to notify, sending email, and producing error logs. (11) The system should have knowledge of when real-time passes and tape recorder dumps will occur and should know that these passes and data transmissions are successful. Once the design criteria were established, the design team split into two groups: one that addressed the tracking, commanding, and health and safety of the science payload and another group that addressed the ground systems and communications aspects of the overall system.
Environmental monitoring, in particular, air monitoring, is a critical need for human space flight. Both monitoring and life support systems have needs for closed loop process feedback and quality control for environmental factors. Monitoring protects the air environment and water supply for the astronaut crew and different sensors help ensure that the habitat falls within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the farther the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. There is an acknowledged need for an event monitor which samples the air continuously and provides near real-time information on changes in the air. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. We are working on a sensor array and new algorithms that will incorporate transient sensor responses in the analysis. Preliminary work has already showed more rapid quantification and identification of analytes and the potential for faster training time of the array. We will look at some of the factors that contribute to demonstrating faster training time for the array. Faster training will decrease the integrated sensor exposure to training analytes, which will also help extend sensor lifetime.
The objectives of this project is to evaluate the capability of the Procedural Reasoning System (PRS) in a typical real-time space shuttle application and to assess its potential for use in the Space Station Freedom. PRS, developed by SRI International, is a result of research in automating the monitoring and control of spacecraft systems. The particular application selected for the present work is the automation of malfunction handling procedures for the Shuttle Remote Manipulator System (SRMS). The SRMS malfunction procedures will be encoded within the PRS framework, a crew interface appropriate to the RMS application will be developed, and the real-time data interface software developed. The resulting PRS will then be integrated with the high-fidelity On-orbit Simulation of the NASA Johnson Space Center's System Engineering Simulator, and tests under various SRMS fault scenarios will be conducted.
Topics covered include: 1) Method to Estimate the Dissolved Air Content in Hydraulic Fluid; 2) Method for Measuring Collimator-Pointing Sensitivity to Temperature Changes; 3) High-Temperature Thermometer Using Cr-Doped GdAlO3 Broadband Luminescence; 4)Metrology Arrangement for Measuring the Positions of Mirrors of a Submillimeter Telescope; 5) On-Wafer S-Parameter Measurements in the 325-508-GHz Band; 6) Reconfigurable Microwave Phase Delay Element for Frequency Reference and Phase-Shifter Applications; 7) High-Speed Isolation Board for Flight Hardware Testing; 8) High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors; 9) 3D Orbit Visualization for Earth-Observing Missions; 10) MaROS: Web Visualization of Mars Orbiting and Landed Assets; 11) RAPID: Collaborative Commanding and Monitoring of Lunar Assets; 12) Image Segmentation, Registration, Compression, and Matching; 13) Image Calibration; 14) Rapid ISS Power Availability Simulator; 15) A Method of Strengthening Composite/Metal Joints; 16) Pre-Finishing of SiC for Optical Applications; 17) Optimization of Indium Bump Morphology for Improved Flip Chip Devices; 18) Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures; 19) Marshall Convergent Spray Formulation Improvement for High Temperatures; 20) Real-Time Deposition Monitor for Ultrathin Conductive Films; 21) Optimized Li-Ion Electrolytes Containing Triphenyl Phosphate as a Flame-Retardant Additive; 22) Radiation-Resistant Hybrid Lotus Effect for Achieving Photoelectrocatalytic Self-Cleaning Anticontamination Coatings; 23) Improved, Low-Stress Economical Submerged Pipeline; 24) Optical Fiber Array Assemblies for Space Flight on the Lunar Reconnaissance Orbiter; 25) Local Leak Detection and Health Monitoring of Pressurized Tanks; 26) Dielectric Covered Planar Antennas at Submillimeter Wavelengths for Terahertz Imaging; 27) Automated Cryocooler Monitor and Control System; 28) Broadband Achromatic Phase Shifter for a Nulling Interferometer; 29) Super Dwarf Wheat for Growth in Confined Spaces; 30) Fine Guidance Sensing for Coronagraphic Observatories; 31) Single-Antenna Temperature- and Humidity-Sounding Microwave Receiver; 32) Multi-Wavelength, Multi-Beam, and Polarization-Sensitive Laser Transmitter for Surface Mapping; 33) Optical Communications Link to Airborne Transceiver; 34) Ascent Heating Thermal Analysis on Spacecraft Adaptor Fairings; 35) Entanglement in Self-Supervised Dynamics; 36) Prioritized LT Codes; 37) Fast Image Texture Classification Using Decision Trees; 38) Constraint Embedding Technique for Multibody System Dynamics; 39) Improved Systematic Pointing Error Model for the DSN Antennas; 40) Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks; 41) More-Accurate Model of Flows in Rocket Injectors; 42) In-Orbit Instrument-Pointing Calibration Using the Moon as a Target; 43) Reliability of Ceramic Column Grid Array Interconnect Packages Under Extreme Temperatures; 44) Six Degrees-of-Freedom Ascent Control for Small-Body Touch and Go; and 45) Optical-Path-Difference Linear Mechanism for the Panchromatic Fourier Transform Spectrometer.
The integrated monitoring and control commercial off-the-shelf system (IMACCS), which demonstrates the feasibility of automating spacecraft monitoring and control activities through the use of state modeling, is described together with its use. The use of the system for the control and ground support of the solar, anomalous and magnetic particle explorer (SAMPEX) spacecraft is considered. A key component of IMACCS is the Altair mission control system which implements finite state modeling as an element of its expert system capability. Using the finite state modeling and state transition capabilities of the Altair mission control system, IMACCS features automated monitoring, routine pass support, anomaly resolution and emergency 'lights on again' response. Automatic orbit determination and the production of typical flight dynamics products exists. These functionalities are described.
A controller-in-the-loop simulation was conducted in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center to investigate the functional allocation aspects associated with ground-based automated separation assurance in a far-term NextGen environment. In this concept, ground-based automation handled the detection and resolution of strategic and tactical conflicts and alerted the controller to deferred situations. The controller was responsible for monitoring the automation and managing situations by exception. This was done in conditions both with and without arrival time constraints across two levels of traffic density. Results showed that although workload increased with an increase in traffic density, it was still manageable in most situations. The number of conflicts increased similarly with a related increase in the issuance of resolution clearances. Although over 99% of conflicts were resolved, operational errors did occur but were tied to local sector complexities. Feedback from the participants revealed that they thought they maintained reasonable situation awareness in this environment, felt that operations were highly acceptable at the lower traffic density level but were less so as it increased, and felt overall that the concept as it was introduced here was a positive step forward to accommodating the more complex environment envisioned as part of NextGen.
Trust and attention allocation are pivotal determinants in human-automation interaction. However, there are scarce empirical findings regarding the relationship between trust and attention allocation. Observations from our previous work suggested there may be a negative correlation between trust in automation and eye movement towards automation, though no formal analysis of these data had been conducted to quantify this relationship. The present meta-analysis examined the relationship between three dimensions of trust in automation (performance, process, and purpose) and visual attention allocation to the automation. Specifically, we applied Cumming’s (2014) meta-analysis technique to combine evidence across three experiments. Results indicated a negative correlation between trust in automation and visual sampling of the automated system monitoring task for performance-based trust, but not for process- or purpose-based trust. These findings suggest that operators scanned the automation’s behavior less frequently when indicating higher performance-based trust towards the automation.
This paper describes the application of Artificial Intelligence techniques for plan generation, plan execution, and plan monitoring to automate a Deep Space Communication Station. This automation allows a Communication station to respond to a set of tracking goals by appropriately reconfiguring the communications hardware and software to provide the requested communications services.
An automated power distribution system testbed for the space station common modules has been developed. It incorporates automated control and monitoring of a utility-type power system. Automated power system switchgear, control and sensor hardware requirements, hardware design, test results, and potential applications are discussed. The system is designed so that the automated control and monitoring of the power system is compatible with both a 208-V, 20-kHz single-phase AC system and a high-voltage (120 to 150 V) DC system.
The Assured Crew Return Vehicle (ACRV) will provide the Space Station Freedom with contingency means of return to earth (1) of one disabled crew member during medical emergencies, (2) of all crew members in case of accidents or failures of SSF systems, and (3) in case of interruption of the Space Shuttle flights. A wide range of vehicle configurations and system approaches are currently under study. The Program requirements focus on minimizing life cycle costs by ensuring simple operations, built-in reliability and maintainability. The ACRV philosophy of embedded operations is based on maximum use of existing facilities, resources and processes, while minimizing the interfaces and impacts to the Space Shuttle and Freedom programs. A preliminary integrated operations concept based on this philosophy and covering the ground, flight, mission support, and landing and recovery operations has been produced. To implement the ACRV operations concept, the underlying approach has been to rely on vehicle autonomy and automation, to the extent possible. Candidate functions and processes which may benefit from current or near-term automation and robotics technologies are identified. These include, but are not limited to, built-in automated ground tests and checkouts; use of the Freedom and the Orbiter remote manipulator systems, for ACRV berthing; automated passive monitoring and performance trend analysis, and periodic active checkouts during dormant periods. The major ACRV operations concept issues as they relate to the use of automation are discussed.
The development of an automated flight test management system (ATMS) as a component of a rapid-prototyping flight research facility for AI-based flight systems concepts is described. The rapid-prototyping facility includes real-time high-fidelity simulators, numeric and symbolic processors, and high-performance research aircraft modified to accept commands for a ground-based remotely augmented vehicle facility. The flight system configuration of the ATMS includes three computers: the TI explorer LX and two GOULD SEL 32/27s.
The goal of this study was to advance understanding and prediction of the impact of circadian rhythm on aspects of complex task performance during unexpected automation failures, and subsequent fault management. Participants trained on two tasks: a process control simulation, featuring automated support; and a multi-tasking platform. Participants then completed one task in a very early morning (circadian night) session, and the other during a late afternoon (circadian day) session. Small effects of time of day were seen on simple components of task performance, but impacts on more demanding components, such as those that occur following an automation failure, were muted relative to previous studies where circadian rhythm was compounded with sleep deprivation and fatigue. Circadian low participants engaged in compensatory strategies, rather than passively monitoring the automation. The findings and implications are discussed in the context of a model that includes the effects of sleep and fatigue factors.
Increased operational autonomy and reduced operating costs have become critical design objectives in next-generation NASA and DoD space programs. The objective is to develop a semi-automated system for intelligent spacecraft operations support. The Spacecraft Operations and Anomaly Resolution System (SOARS) is presented as a standardized, model-based architecture for performing High-Level Tasking, Status Monitoring and automated Procedure Execution Control for a variety of spacecraft. The particular focus is on the Procedure Execution Control module. A hierarchical procedure network is proposed as the fundamental means for specifying and representing arbitrary operational procedures. A separate procedure interpreter controls automatic execution of the procedure, taking into account the current status of the spacecraft as maintained in an object-oriented spacecraft model.
The rapid advance of cockpit automation in the last decade has outstripped the ability of the human factors profession to understand the changes in human functions required. High technology cockpits require less physical (observable) workload, but are highly demanding of cognitive functions such as planning, alternative selection, and monitoring. Furthermore, automation creates opportunity for new and more serious forms of human error, and many pilots are concerned about the possibility of complacency affecting their performance. On the positive side, the equipment works as advertized with high reliability, offering highly efficient, computer-based flight. These findings from the cockpit studies probably apply equally to other industries, such as nuclear power production, other modes of transportation, medicine, and manufacturing, all of which traditionally have looked to aviation for technological leadership. The challenge to the human factors profession is to aid designers, operators, and training departments in exploiting the positive side of automation, while seeking solutions to the negative side. Viewgraphs are given.