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At least 163 records · Page 9

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NASA NTRS2002

A Framework for Creating a Function-based Design Tool for Failure Mode Identification

Knowledge of potential failure modes during design is critical for prevention of failures. Currently industries use procedures such as Failure Modes and Effects Analysis (FMEA), Fault Tree analysis, or Failure Modes, Effects and Criticality analysis (FMECA), as well as knowledge and experience, to determine potential failure modes. When new products are being developed there is often a lack of sufficient knowledge of potential failure mode and/or a lack of sufficient experience to identify all failure modes. This gives rise to a situation in which engineers are unable to extract maximum benefits from the above procedures. This work describes a function-based failure identification methodology, which would act as a storehouse of information and experience, providing useful information about the potential failure modes for the design under consideration, as well as enhancing the usefulness of procedures like FMEA. As an example, the method is applied to fifteen products and the benefits are illustrated.

Arunajadai, Srikesh G.↗

NASA NTRS1987

A research program in advanced information systems

Topics addressed cover: identification of large space structure dynamics; special-purpose architectures for computational fluid dynamics; fault-tolerant processor architectures; data flow techniques; software specification and verification tools; management of software development; software environment for concurrent computing; and parallel algorithms and architectures for the solution of partial differential equations.

Vandervelde, Wallace E.↗

NASA NTRS1988

Graph-based real-time fault diagnostics

A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components.

Padalkar, S.↗

NASA NTRS1992

Failure behavior identification for a space antenna via neural networks

By using neural networks, a method for the failure behavior identification of a space antenna model is investigated. The proposed method uses three stages. If a fault is suspected by the first stage of fault detection, a diagnostic test is performed on the antenna. The diagnostic test results are used by the second and third stages to identify which fault occurred and to diagnose the extent of the fault, respectively. The first stage uses a multilayer perceptron, the second stage uses a multilayer perceptron and neural networks trained with the quadratic optimization algorithm, a novel training procedure, and the third stage uses backpropagation trained neural networks.

Sartori, Michael A.↗

NASA NTRS1982

A study of the United States coal resources

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.

Ferm, J. C.↗

NASA NTRS1993

Nuclear propulsion control and health monitoring

An integrated control and health monitoring architecture is being developed for the Pratt & Whitney XNR2000 nuclear rocket. Current work includes further development of the dynamic simulation modeling and the identification and configuration of low level controllers to give desirable performance for the various operating modes and faulted conditions. Artificial intelligence and knowledge processing technologies need to be investigated and applied in the development of an intelligent supervisory controller module for this control architecture.

Walter, P. B.↗

NASA NTRS1973

Identification and interpretation of tectonic features from ERTS-1 imagery

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.

Abdel-Gawad, M.↗

NASA NTRS1990

Software reliability through fault-avoidance and fault-tolerance

The use of back-to-back, or comparison, testing for regression test or porting is examined. The efficiency and the cost of the strategy is compared with manual and table-driven single version testing. Some of the key parameters that influence the efficiency and the cost of the approach are the failure identification effort during single version program testing, the extent of implemented changes, the nature of the regression test data (e.g., random), and the nature of the inter-version failure correlation and fault-masking. The advantages and disadvantages of the technique are discussed, together with some suggestions concerning its practical use.

Vouk, Mladen A.↗

NASA NTRS1992

Links between N-modular redundancy and the theory of error-correcting codes

N-Modular Redundancy (NMR) is one of the best known fault tolerance techniques. Replication of a module to achieve fault tolerance is in some ways analogous to the use of a repetition code where an information symbol is replicated as parity symbols in a codeword. Linear Error-Correcting Codes (ECC) use linear combinations of information symbols as parity symbols which are used to generate syndromes for error patterns. These observations indicate links between the theory of ECC and the use of hardware redundancy for fault tolerance. In this paper, we explore some of these links and show examples of NMR systems where identification of good and failed elements is accomplished in a manner similar to error correction using linear ECC's.

Bobin, V.↗

NASA NTRS2002

Flight Evaluation of the Army/NASA Variable Stability Fly-by-Wire Rotorcraft Aircrew Systems Concept Airborne Laboratory (RASCAL) JUH-60A

NASA Ames Research Center and the U.S. Army Aeroflight dynamics Directorate (AFDD) have performed initial flight evaluations of the Research Flight Control System (RFCS) integrated into the Army/NASA Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) JUH-GOA. The highly modified JUH-GOA Black Hawk helicopter is a full authority, high bandwidth, variable stability, in-flight simulator designed to support development of advanced flight control, sensor, and integrated display and control technologies in a fail safe environment. Preparation for flight test required an extensive hazard analysis and ground testing to ensure proper system operation. A hardware in the loop development facility was utilized to evaluate control law stability following software changes, assess servo hardover upset conditions during manual and monitor disengagements and provide pilot familiarization of test techniques and software changes prior to flight. First engagement of the RFCS was conducted on 31 Aug 2001. RFCS transfer system operation, envelope expansion and a limited rate monitor evaluation have been completed with low bandwidth and model following control laws. The presentation will discuss the following - System overview including aircraft modifications and integrated development facilities used with the RASCAL facility. - Preliminary hazard identification and mitigation prior to flight test. - Ground testing used to qualify the RFCS transfer system and verify fault monitor operation. - Flight test results of low-bandwidth and model following control law evaluations including maneuver agility, control limitations, fault monitor reliability, and recovery from manual and monitor disengagement. - Lessons learned including test techniques using a passive three-axis sidearm controller, the value of the development facility in reducing risk and crew coordination issues related to the operation of a full authority, variable stability platform. - Future research and modifications planned for the RASCAL aircraft.

Dave Arterburn↗

NASA NTRS1989

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

Gupta, U. K.↗

NASA NTRS1973

Identification of geostructures of continental crust, particularly as they relate to mineral resource evaluation

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.

Gryc, G.↗

NASA NTRS1974

Identification and interpretation of tectonic features from Skylab imagery

The author has identified the following significant results. A remarkable system of northwest and west-northwest trending faults was found to continue from eastern California into southwestern Arizona. The most significant is a fault belt which extends from west of Marble Mountains (southeastern California) across the Colorado River at Parker Valley towards Silver Bell Mountains, southern Arizona.

Abdel-Gawad, M.↗

NASA NTRS1990

An expert system for fault diagnosis in a Space Shuttle main engine

The detection and diagnosis of SSME faults in an early stage is important in order to allow enough time for fault preventive or corrective measurements. Since most of the faults in a complex system like SSME develop rapidly, early detection and diagnosis of faults is critical for the survival of space vehicles. An expert system has been designed for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations. This paper describes an innovative machine learning approach which is employed for the automatic training of this expert system.

Ali, Moonis↗

NASA NTRS1991

Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design

Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design.

Malin, Jane T.↗

NASA NTRS2002

Failure Mode Identification Through Clustering Analysis

Research has shown that nearly 80% of the costs and problems are created in product development and that cost and quality are essentially designed into products in the conceptual stage. Currently, failure identification procedures (such as FMEA (Failure Modes and Effects Analysis), FMECA (Failure Modes, Effects and Criticality Analysis) and FTA (Fault Tree Analysis)) and design of experiments are being used for quality control and for the detection of potential failure modes during the detail design stage or post-product launch. Though all of these methods have their own advantages, they do not give information as to what are the predominant failures that a designer should focus on while designing a product. This work uses a functional approach to identify failure modes, which hypothesizes that similarities exist between different failure modes based on the functionality of the product/component. In this paper, a statistical clustering procedure is proposed to retrieve information on the set of predominant failures that a function experiences. The various stages of the methodology are illustrated using a hypothetical design example.

Arunajadai, Srikesh G.↗

NASA NTRS2015

Fault Management Architectures and the Challenges of Providing Software Assurance

The satellite systems Fault Management (FM) is focused on safety, the preservation of assets, and maintaining the desired functionality of the system. How FM is implemented varies among missions. Common to most is system complexity due to a need to establish a multi-dimensional structure across hardware, software and operations. This structure is necessary to identify and respond to system faults, mitigate technical risks and ensure operational continuity. These architecture, implementation and software assurance efforts increase with mission complexity. Because FM is a systems engineering discipline with a distributed implementation, providing efficient and effective verification and validation (VV) is challenging. A breakout session at the 2012 NASA Independent Verification Validation (IVV) Annual Workshop titled VV of Fault Management: Challenges and Successes exposed these issues in terms of VV for a representative set of architectures. NASA's IVV is funded by NASA's Software Assurance Research Program (SARP) in partnership with NASA's Jet Propulsion Laboratory (JPL) to extend the work performed at the Workshop session. NASA IVV will extract FM architectures across the IVV portfolio and evaluate the data set for robustness, assess visibility for validation and test, and define software assurance methods that could be applied to the various architectures and designs. This work focuses efforts on FM architectures from critical and complex projects within NASA. The identification of particular FM architectures, visibility, and associated VVIVV techniques provides a data set that can enable higher assurance that a satellite system will adequately detect and respond to adverse conditions. Ultimately, results from this activity will be incorporated into the NASA Fault Management Handbook providing dissemination across NASA, other agencies and the satellite community. This paper discusses the approach taken to perform the evaluations and preliminary findings from the research including identification of FM architectures, visibility observations, and methods utilized for VVIVV.

Fault Management↗

NASA NTRS2013

A System for Fault Management for NASA's Deep Space Habitat

NASA's 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.

Fault management↗