Combinatorial techniques for fault identification in multi-terminal networks.
Fault identification and diagnosis in multiterminal devices by combinatorial techniques for computer programming
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Fault identification and diagnosis in multiterminal devices by combinatorial techniques for computer programming
Combinatorial techniques for fault identification in multiterminal networks, discussing algorithms for computer oriented procedures and computer program flow chart
The space station module power management and distribution (SSM/PMAD) breadboard models power distribution and management, including scheduling, load prioritization, and a fault detection, identification, and recovery (FDIR) system within a Space Station Freedom habitation or laboratory module. This 120 VDC system is capable of distributing up to 30 kW of power among more than 25 loads. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level consists of fast, simple (from a computing standpoint) switchgear that is capable of quickly safing the system. At the next level are local load center processors, (LLP's) which execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. Above the LLP's are three cooperating artificial intelligence (AI) systems which manage load prioritizations, load scheduling, load shedding, and fault recovery and management. Recent upgrades to hardware and modifications to software at both the LLP and AI system levels promise a drastic increase in speed, a significant increase in functionality and reliability, and potential for further examination of advanced automation techniques. The background, SSM/PMAD, interface to the Lewis Research Center test bed, the large autonomous spacecraft electrical power system, and future plans are discussed.
Review of the long-life and minimum-turnaround-maintenance features in the design of the Space Shuttle Orbiter main engine aimed at reducing the latter's field operating costs. These features include the regeneratively cooled hot-gas system selected, the provision of additional fatigue margins in the design of rotating machinery elements, and employment of a proven approach to engine condition monitoring for fault detection and identification.
Automating prelaunch diagnostics for launch vehicles offers three potential benefits. First, it potentially improves safety by detecting faults that might otherwise have been missed so that they can be corrected before launch. Second, it potentially reduces launch delays by more quickly diagnosing the cause of anomalies that occur during prelaunch processing. Reducing launch delays will be critical to the success of NASA's planned future missions that require in-orbit rendezvous. Third, it potentially reduces costs by reducing both launch delays and the number of people needed to monitor the prelaunch process. NASA is currently developing the Ares I launch vehicle to bring the Orion capsule and its crew of four astronauts to low-earth orbit on their way to the moon. Ares I-X will be the first unmanned test flight of Ares I. It is scheduled to launch on October 27, 2009. The Ares I-X Ground Diagnostic Prototype is a prototype ground diagnostic system that will provide anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage thrust vector control (TVC) and for the associated ground hydraulics while it is in the Vehicle Assembly Building (VAB) at John F. Kennedy Space Center (KSC) and on the launch pad. It will serve as a prototype for a future operational ground diagnostic system for Ares I. The prototype combines three existing diagnostic tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool that is commercially produced by Qualtech Systems, Inc. It uses a qualitative model of failure propagation to perform fault isolation and diagnostics. We adapted an existing TEAMS model of the TVC to use for diagnostics and developed a TEAMS model of the ground hydraulics. The second tool, Spacecraft Health Inference Engine (SHINE), is a rule-based expert system developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification. The prototype uses the outputs of SHINE as inputs to TEAMS. The third tool, the Inductive Monitoring System (IMS), is an anomaly detection tool developed at NASA Ames Research Center and is currently used to monitor the International Space Station Control Moment Gyroscopes. IMS automatically "learns" a model of historical nominal data in the form of a set of clusters and signals an alarm when new data fails to match this model. IMS offers the potential to detect faults that have not been modeled. The three tools have been integrated and deployed to Hangar AE at KSC where they interface with live data from the Ares I-X vehicle and from the ground hydraulics. The outputs of the tools are displayed on a console in Hangar AE, one of the locations from which the Ares I-X launch will be monitored. In a previous publication, we discussed how we selected the three tools based primarily on their ability to be certified for human spaceflight and described our plans for the prototype. This abstract is due October 23, 2009, and the Ares I-X launch is currently scheduled for October 27, 2009. If this abstract is accepted, then the full paper will describe how the prototype performed before the launch. It will include an analysis of the prototype's accuracy, including false-positive rates, false-negative rates, and receiver operating characteristics (ROC) curves. It will also include a description of the prototype's computational requirements, including CPU usage, main memory usage, and disk usage. If the prototype detects any faults during the prelaunch period then the paper will include a description of those faults. Similarly, if the prototype has any false alarms then the paper will describe them and will attempt to explain their causes. Also, the paper will describe the three tools and how they are used in the prototype. It will include a description of the TEAMS models of the Ares I-X first-stage TVC and associated ground hydraulics and how we adapted the TVC model for use in real-time diagnostics. It will describe the SHINE rules used for fault detection and mode identification and the software architecture that interfaces the various pieces of existing software that are part of the prototype to one another. It will describe how we selected the sensor values and commands that were used to train the IMS model and how we optimized the number of clusters in the IMS model. It will include screen shots of the graphical display that we developed in Java to display the outputs of the three tools. Because Ares I-X data was not yet available to us while we were developing the prototype, we used historical data from the Space Shuttle's Solid Rocket Booster (SRB) TVCs and the associated ground hydraulics to train IMS and to test the entire prototype. Because most of the failure modes that we modeled have never occurred in the Shuttle we inserted simulated failures into the Shuttle data. The Ares I-X first-stage TVC is very similar to the SRB TVC and we expect the data will be very similar. After the launch, we will determine how similar the data actually is and report how any differences in the data affected the diagnostic accuracy of the prototype. Finally, although we did not get the prototype certified, we designed it in a way that it could be certified and wrote a preliminary certification plan. The paper will include a brief summary of how we considered the need for certification in the design of the prototype, how we tested the prototype before deploying it to Hangar AE, and how we would propose to get it certified if it were deployed as an operational system. The paper will conclude with a description of some of the challenges we faced and some of the lessons learned in developing and deploying the prototype.
The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.
The author has identifed the following significant results. ERTS-1 imagery provided evidence for the existence of short transverse fault segments lodged between faults of the San Andreas system in the Coast Ranges, California. They indicate that an early episode of transverse shear has affected the Coast Ranges prior to the establishment of the present San Andreas fault. The fault has been offset by transverse faults of the Transverse Ranges. It appears feasible to identify from ERTS-1 imagery geomorphic criteria of recent fault movements. Plots of historic earthquakes in the Coast Ranges and western Transverse Ranges show clusters in areas where structures are complicated by interaction of tow active fault systems. A fault lineament apparently not previously mapped was identified in the Uinta Mountains, Utah. Part of the lineament show evidence of recent faulting which corresponds to a moderate earthquake cluster.
The author has identified the following significant results. The broad synoptic view of the images allowed easy identification of circular features and major fault traces in low lying areas. Sedimentary units were delineated in accordance with the prevailing rock types and where applicable the folding characteristics. Igneous units could easily be differentiated by tone, degree of fracturing, texture, and drainage pattern. The larger fold structures, anticlinoriums and synclinoriums, of the younger sediments on the eastern edge of the central belt could also be easily delineated.
The author has identified the following significant results. Many criteria of active or recent fault movements are observable in the imagery. It was observed that where earthquake epicenter clusters occur, evidence of recent fault movements is generally observed. The opposite was not necessarily true as there are areas where evidence of recent faulting is observed, often along major known faults which are peculiarly devoid of significant seismicity. A tentative conclusion is that the seismicity pattern alone can often be a misleading criteria for potential earthquake hazards. The feasibility of recognizing geomorphic criteria of recent fault movement from ERTS-1 imagery suggests that ERTS imagery should be used to map potentially active faults and utilize this data to develop better criteria for the identification of areas prone to future earthquakes. An apparent correlation was observed between the distribution of mercury deposits in the California Coast Range Province and transverse fault zones trending west-northwest oblique to the trend of the San Andreas system. The significance of this correlation and the full extent of its implication on mercury exploration is under study.
The author has identified the following significant results. Skylab photographs were utilized to study faults and tectonic lines in selected areas of the U.S. Southwest. Emphasis was on elements of the Texas Zone in the Mojave Desert and the tectonic intersection in southern Nevada. Transverse faults believed to represent the continuation of the Texas Zone were found to be anomalous in strike. This suggests that the Mojave Desert block was rotated counterclockwise as a unit with the Sierra Nevada. Left-lateral strike-slip faults in Lake Mead area are interpreted as elements of the Wasatch tectonic zone; their anomalous trend indicates that the Lake Mead area has rotated clockwise with the Colorado Plateau. A tectonic model relating major fault zones to fragmentation and rotation of crustal blocks was developed. Detailed correlation of the high resolution S190B metric camera photographs with U-2 photographs and geologic maps demonstrates the feasibility of utilizing S190B photographs for the identification of geomorphic features associated with recent and active faults and for the assessment of seismic hazards.
The author has identified the following significant results. The fault pattern in the southern Nevada tectonic intersection and adjacent Mojave block was found to be consistent with a model partly suggested by Hamilton and Myers (1966). The model has the following basic elements: (1) a major Laramide left-lateral shear on the Texas Zone, (2) counterclockwise rotation of the Sierra Nevada-Klamath Mountain block, (3) clockwise rotation of the Colorado Plateau, and (4) crustal extension and intrusion of volcanics in Nevada.
The author has identified the following significant results. An important fault zone, which is strongly suspected of being seismically active, was identified on RBV images, ERTS E-1013-17305 (101, 201, and 301), in northeastern Utah. This fault zone is not shown on the Geological Map of the United States nor on the Tectonic Map of North America. When the epicenters of historic earthquakes and their magnitudes were plotted on an overlay corresponding to the scene, a major earthquake cluster up to magnitude 4.9 was found through which the fault zone passes. This suspected active fault zone runs in a northwest-southwest direction cutting across the Patmos Mountains and the southwestern side of the East Tavaputs Plateau from near the junction of the Colorado River with the Dolores River to and beyond the town of Dragerton, Utah. The fault zone which will subsequently be referred to as the Dragerton fault zone appears to be an element of a major tectonic lineament which includes the Moab fault, Salt Valley, Spanish and Lisbon Valleys. Because of the limited imagery coverage received so far, the extent of this lineament or its tectonic significance cannot be ascertained. It is suspected, however, that it constitutes a major crustal break in the Colorado Plateau.
The author has identified the following significant results. The transverse faults observed in the central Coast Ranges of California are believed to represent the remnants of a major system of shear faults older than the San Andreas system. The transverse shear system is believed to have developed in the Mesozoic when the Pacific Plate was advancing under the North American Plate. Shear faults thus developed due to unequal rates of underthrusting. This tectonic model indicates that the intrusive belt of the proto-Sierra Nevada and the belt of eugeosynclinal sedimentary belt (Franciscan group) which lay to the west were both subjected to regional left-handed shear. Later development of the San Andreas system as transform faults of the East Pacific Rise changes the tectonic style to right-lateral tangential. The model explains the peculiar distribution of the Franciscan rocks in the Diablo Range east of the San Andreas fault and in Santa Lucia Range west of Nacimiento fault and the presence of Sierra Nevada type granitic blocks in between the two faults in the Salinia block. This model is also consistent with an analysis of the Texas and Parras shears which indicates that the southwestern part of North America has been subjected to a major left-lateral regional shear before the development of the San Andreas fault system.
Analytical redundancy is applied to the pitch axis of an aircraft to enhance sensor fault detection. Three different designs based on monitoring Kalman filter residuals or likelihood functions were developed. Sensor failures were simulated to evaluate the performance of the algorithms on a nonlinear simulation of an F-8C aircraft. Based on requirements for sensor fault detection and preliminary simulator performance it is concluded that these algorithms have the potential for reducing the level of sensor redundancy in a digital flight control system without compromising performance.
The author has identified the following significant results. Surface indications of recent faulting are generally observed in EREP S190B photographs. Comparison of secondary roads (asphalt and dirt) registered in EREP and U-2 photographs together with field measurements shows that dirt and asphalt roads about seven meters wide can be detected in EREP S190B photographs where sufficient contrast exists between the tone of the road surface and surrounding terrain. In low contrast cases, roads more than ten meters wide could not be detected.
Geologically significant coal resources were identified. Statistically controlled tonnage estimates for each resource type were prepared. Particular emphasis was placed on the identification and description of coals in terms of seam thickness, inclination, depth of cover, discontinuities caused by faulting and igneous intrusion, and occurrence as isolated or multiseam deposits. The national resource was organized into six major coal provinces: the Appalachian Plateau, the Interior Basins, the Gulf Coastal Plain, the Rocky Mountain Basins, the High Plains, and North Alaska. Each basin within a province was blocked into subareas of homogeneous coal thickness. Total coal tonnage for a subarea was estimated from an analysis of the cumulative coal thickness derived from borehole or surface section records and subsequently categorized in terms of seam thickness, dip, overburden, multiseam proportions, coal quality, and tonnage impacted by severe faulting and igneous intrusions. Confidence intervals were calculated for both subarea and basin tonnage estimates.
The author has identified the following significant results. The spatial relation of mercury deposits and faults in California coast ranges suggests regional structural control whereby the transverse faults and associated zones of weakness provided easy conduits for the ascent of hydrothermal solutions and emplacement of mercury ore. If proved valid, this relation identifies transverse fault zones as favorable structural guides for mercury exploration.
The author has identified the following significant results. The southeastward continuation of a fault that has been mapped in the vicinity of Dan Creek, Alaska, shows up as a lineament on ERTS-1 image 1043-20163 that can be traced for more than 50 miles southeastward to beyond the Alaska-Canada boundary. The lineament probably reflects a major fault that is significant in understanding the complicated tectonics of the Wrangell Mountains-Saint Elias Mountains complex. From a study of the ERTS-1 image, low level vertical photography, and limited field work in the largely unmapped region, E.M. Mackevett, Jr., speculates that the eastern part of the fault may mark the southern boundary of a mild-Paleozoic metamorphic terrane that constitutes the westernmost known extent of the Alexander terrane of Berg, Jones, and Richter (1972) and correlates with the Kaskawulsh Group in Canada. This terrane, which consists dominantly of marble, was recognized during 1972 reconnaissance mapping in the eastcentral part of the McCarthy quadrangle by MacKevett, D.L. Jones, and D.H. Richter and contrasts strongly with the dominantly volcanic and volcanoclastic terrane of Pennsylvanian and Permian age that forms the basement in most of the McCarthy quadrangle.