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Results for “Automated Fault Detection and Diagnosis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

A two-level structure for advanced space power system automation

The tasks to be carried out during the three-year project period are: (1) performing extensive simulation using existing mathematical models to build a specific knowledge base of the operating characteristics of space power systems; (2) carrying out the necessary basic research on hierarchical control structures, real-time quantitative algorithms, and decision-theoretic procedures; (3) developing a two-level automation scheme for fault detection and diagnosis, maintenance and restoration scheduling, and load management; and (4) testing and demonstration. The outlines of the proposed system structure that served as a master plan for this project, work accomplished, concluding remarks, and ideas for future work are also addressed.

Loparo, Kenneth A.↗
NASA NTRS2013

Putting Integrated Systems Health Management Capabilities to Work: Development of an Advanced Caution and Warning System for Next-Generation Crewed Spacecraft Missions

Integrated System Health Management (ISHM) technologies have advanced to the point where they can provide significant automated assistance with real-time fault detection, diagnosis, guided troubleshooting, and failure consequence assessment. To exploit these capabilities in actual operational environments, however, ISHM information must be integrated into operational concepts and associated information displays in ways that enable human operators to process and understand the ISHM system information rapidly and effectively. In this paper, we explore these design issues in the context of an advanced caution and warning system (ACAWS) for next-generation crewed spacecraft missions. User interface concepts for depicting failure diagnoses, failure effects, redundancy loss, "what-if" failure analysis scenarios, and resolution of ambiguity groups are discussed and illustrated.

integrated system management↗
NASA NTRS1987

An evaluation of a real-time fault diagnosis expert system for aircraft applications

A fault monitoring and diagnosis expert system called Faultfinder was conceived and developed to detect and diagnose in-flight failures in an aircraft. Faultfinder is an automated intelligent aid whose purpose is to assist the flight crew in fault monitoring, fault diagnosis, and recovery planning. The present implementation of this concept performs monitoring and diagnosis for a generic aircraft's propulsion and hydraulic subsystems. This implementation is capable of detecting and diagnosing failures of known and unknown (i.e., unforseeable) type in a real-time environment. Faultfinder uses both rule-based and model-based reasoning strategies which operate on causal, temporal, and qualitative information. A preliminary evaluation is made of the diagnostic concepts implemented in Faultfinder. The evaluation used actual aircraft accident and incident cases which were simulated to assess the effectiveness of Faultfinder in detecting and diagnosing failures. Results of this evaluation, together with the description of the current Faultfinder implementation, are presented.

Schutte, Paul C.↗
NASA NTRS1993

Implementing a real time reasoning system for robust diagnosis

The objective of the Thermal Control System Automation Project (TCSAP) is to develop an advanced fault detection, isolation, and recovery (FDIR) capability for use on the Space Station Freedom (SSF) External Active Thermal Control System (EATCS). Real-time monitoring, control, and diagnosis of the EATCS will be performed with a knowledge based system (KBS). Implementation issues for the current version of the KBS are discussed.

Hill, Tim↗
NASA NTRS1990

Launching AI in NASA ground systems

This paper will discuss recent operational successes in implementing expert systems to support the complex functions of NASA mission control systems at the Goddard Space Flight Center, including fault detection and diagnosis for real time and engineering analysis functions in the Cosmic Background Explorer and Gamma Ray Observatory missions and automation of resource planning and scheduling functions for various missions. It will also discuss ongoing developments and prototypes that will lead to increasingly sophisticated applications of artificial intelligence. These include the use of neural networks to perform telemetry monitoring functions, the implementation of generic expert system shells that can be customized to telemetry handling functions specific to NASA control centers, the applications of AI in training and user support, the long-term potential of implementing systems based around distributed, cooperative problem solving, and the use of AI to control and assist system development activities.

Perkins, Dorothy C.↗
NASA NTRS2011

An Examination of Commercial Aviation Accidents and Incidents Related to Integrated Vehicle Health Management

The Integrated Vehicle Health Management (IVHM) Project is one of the four projects within the National Aeronautics and Space Administration's (NASA) Aviation Safety Program (AvSafe). The IVHM Project conducts research to develop validated tools and technologies for automated detection, diagnosis, and prognosis that enable mitigation of adverse events during flight. Adverse events include those that arise from system, subsystem, or component failure, faults, and malfunctions due to damage, degradation, or environmental hazards that occur during flight. Determining the causal factors and adverse events related to IVHM technologies will help in the formulation of research requirements and establish a list of example adverse conditions against which IVHM technologies can be evaluated. This paper documents the results of an examination of the most recent statistical/prognostic accident and incident data that is available from the Aviation Safety Information Analysis and Sharing (ASIAS) System to determine the causal factors of system/component failures and/or malfunctions in U.S. commercial aviation accidents and incidents.

Reveley, Mary S.↗
NASA NTRS1978

Fault-tolerant building-block computer study

Ultra-reliable core computers are required for improving the reliability of complex military systems. Such computers can provide reliable fault diagnosis, failure circumvention, and, in some cases serve as an automated repairman for their host systems. A small set of building-block circuits which can be implemented as single very large integration devices, and which can be used with off-the-shelf microprocessors and memories to build self checking computer modules (SCCM) is described. Each SCCM is a microcomputer which is capable of detecting its own faults during normal operation and is described to communicate with other identical modules over one or more Mil Standard 1553A buses. Several SCCMs can be connected into a network with backup spares to provide fault-tolerant operation, i.e. automated recovery from faults. Alternative fault-tolerant SCCM configurations are discussed along with the cost and reliability associated with their implementation.

Rennels, D. A.↗
NASA NTRS1990

Applications of AI for automated monitoring - The SHARP system

This paper describes a software system which utilizes artificial intelligence technology to automate several real-time mission operations functions. The paper gives an overview of Voyager spacecraft telecommunications operations at the Jet Propulsion Laboratory to highlight requirements for operations automation in the area of real-time monitoring and analysis. A knowledge-based system, called the 'Spacecraft Health Automated Reasoning Prototype' (SHARP), was developed to explore methods for automated ground data system health and status analysis. The prototype system was applied to Voyager spacecraft telecommunications operations, and installed in the Voyager real-time telecommunications operations area during the spacecraft's encounter with the planet Neptune. The paper reviews the design of the fault detection and diagnosis portions of SHARP, and discusses the performance of SHARP during the encounter. Two follow-on systems based on SHARP which are now in development are also discussed.

Atkinson, David J.↗
NASA NTRS1981

Traveling-wave maser, closed cycle refrigerator automation

At the present time all traveling-wave maser and closed-cycle refrigerator system (TWM-CCR) and their power supply and helium compressor assemblies are operated manually. Many man-hours are required of highly trained and experienced operators, resulting in high operator cost. Of greater importance are the problems of unpredictable failure and long downtimes. Since field performance is not monitored, system degradation is detected only when it has progressed to the point of catastrophic failure. Without the aid of performance histories, failure diagnosis is arduous and slow. Rational and functional requirements for the TWM-CCR Automation project are the following: (1) to improve reliability and reduce downtime by providing unattended monitor and control, alarm and fault location, failure prediction and self-corrective action; (2) to reduce operator cost by providing automatic tuning and cooldown procedures; and (3) to improve system operations and development by providing the needed engineering data.

Mcneil, J. A.↗
NASA NTRS2007

POD Model Reconstruction for Gray-Box Fault Detection

Proper orthogonal decomposition (POD) is the mathematical basis of a method of constructing low-order mathematical models for the "gray-box" fault-detection algorithm that is a component of a diagnostic system known as beacon-based exception analysis for multi-missions (BEAM). POD has been successfully applied in reducing computational complexity by generating simple models that can be used for control and simulation for complex systems such as fluid flows. In the present application to BEAM, POD brings the same benefits to automated diagnosis. BEAM is a method of real-time or offline, automated diagnosis of a complex dynamic system.The gray-box approach makes it possible to utilize incomplete or approximate knowledge of the dynamics of the system that one seeks to diagnose. In the gray-box approach, a deterministic model of the system is used to filter a time series of system sensor data to remove the deterministic components of the time series from further examination. What is left after the filtering operation is a time series of residual quantities that represent the unknown (or at least unmodeled) aspects of the behavior of the system. Stochastic modeling techniques are then applied to the residual time series. The procedure for detecting abnormal behavior of the system then becomes one of looking for statistical differences between the residual time series and the predictions of the stochastic model.

Park, Han↗
NASA NTRS2012

Model-Based Fault Diagnosis: Performing Root Cause and Impact Analyses in Real Time

Generic, object-oriented fault models, built according to causal-directed graph theory, have been integrated into an overall software architecture dedicated to monitoring and predicting the health of mission- critical systems. Processing over the generic fault models is triggered by event detection logic that is defined according to the specific functional requirements of the system and its components. Once triggered, the fault models provide an automated way for performing both upstream root cause analysis (RCA), and for predicting downstream effects or impact analysis. The methodology has been applied to integrated system health management (ISHM) implementations at NASA SSC's Rocket Engine Test Stands (RETS).

Figueroa, Jorge F.↗
NASA NTRS1993

Model-based reasoning for power system management using KATE and the SSM/PMAD

The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications.

Morris, Robert A.↗
NASA NTRS1990

Distributed systems status and control

Concepts are investigated for an automated status and control system for a distributed processing environment. System characteristics, data requirements for health assessment, data acquisition methods, system diagnosis methods and control methods were investigated in an attempt to determine the high-level requirements for a system which can be used to assess the health of a distributed processing system and implement control procedures to maintain an accepted level of health for the system. A potential concept for automated status and control includes the use of expert system techniques to assess the health of the system, detect and diagnose faults, and initiate or recommend actions to correct the faults. Therefore, this research included the investigation of methods by which expert systems were developed for real-time environments and distributed systems. The focus is on the features required by real-time expert systems and the tools available to develop real-time expert systems.

Kreidler, David↗
NASA NTRS2006

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗
NASA NTRS2018

Automated Contingency Management for Water Recycling System

To enable effective management, planning, and operations for future missions that involve a crewed space habitat, operational support must be migrated from Earth to the habitat. Intelligent System Health Management technologies (ISHM) promise to enable the future space habitats to increase the safety and mission success while minimizing operational risks. In this paper, Water Recycling System (WRS) deployed at NASA Ames Research Center's Sustainability Base is used for verification and validation of the proposed solution. Our work includes the development of the WRS simulation model based on its dynamic physical characteristics and the design of Automatic Contingency Management (ACM) framework that integrates fault diagnosis and optimization. In WRS modeling, a nominal model with fault injectors is developed. Fault detection and isolation techniques are then developed for isolating causes and identifying the severity of the faults. Dynamic Programming (DP) based fault mitigation strategies are designed to accommodate the faults in the system. A series of simulations are presented with different fault modes and the results indicate that the proposed ACM system can alleviate the fault in the WRS optimally regarding energy consumption and effects of the fault.

Systems Health Management↗
NASA NTRS1992

Expert systems for automated maintenance of a Mars oxygen production system

Application of expert system concepts to a breadboard Mars oxygen processor unit have been studied and tested. The research was directed toward developing the methodology required to enable autonomous operation and control of these simple chemical processors at Mars. Failure detection and isolation was the key area of concern, and schemes using forward chaining, backward chaining, knowledge-based expert systems, and rule-based expert systems were examined. Tests and simulations were conducted that investigated self-health checkout, emergency shutdown, and fault detection, in addition to normal control activities. A dynamic system model was developed using the Bond-Graph technique. The dynamic model agreed well with tests involving sudden reductions in throughput. However, nonlinear effects were observed during tests that incorporated step function increases in flow variables. Computer simulations and experiments have demonstrated the feasibility of expert systems utilizing rule-based diagnosis and decision-making algorithms.

Huang, Jen-Kuang↗
NASA NTRS2003

Issues and Concerns in Robotic Drilling

Exploration of the Martian subsurface will be essential in the search for life and water, given the desiccated and highly oxidized conditions on the surface. Discovery of these, at least in non-fossil form, is unlikely without drilling or other physical access to the subsurface. Hence subsurface access will be critical for both future in-situ science and Mars sample return. Drilling applications present many new challenges for diagnosis and control technology. Traditionally, diagnosis has concentrated on determining the internal state of a system, and detecting failures of system components. In the case of drilling applications, an additional challenge is to diagnose the interactions between the drill and its environment. This is necessary because particular observations of the drilling operation may be consistent with a number of possible problems, including faults in the equipment, but also changes in the material being drilled (for example, from rock to ice). The diagnosis of a particular observation may also depend on knowledge of geological formations previously encountered during drilling, and different remedial actions may be required for each diagnosis. Current 2009 Mars mission scenarios call for no more than 33 sols to be spent drilling. Yet they also call for a baseline of two 2m-deep holes in each of three target areas, for a total of six drilling operations. Using current levels of automation, it is estimated that 15-16 sols would be required to drill each hole. As a result of this, either the drilling part of the mission plan will need to be severely downscoped to no more than two holes total, or on-board automation and robotics must be increased in order to reduce the number of sols required per hole by removing ground control from the drilling control loop. This lecture will discuss salient issues and concerns of robotic drilling automation compares with other applications, and implementation constraints.

Glass, Brian↗
NASA NTRS2009

Lightning Pin Injection Testing on MOSFETS

Lightning transients were pin-injected into metal-oxide-semiconductor field-effect transistors (MOSFETs) to induce fault modes. This report documents the test process and results, and provides a basis for subsequent lightning tests. MOSFETs may be present in DC-DC power supplies and electromechanical actuator circuits that may be used on board aircraft. Results show that unprotected MOSFET Gates are susceptible to failure, even when installed in systems in well-shielded and partial-shielded locations. MOSFET Drains and Sources are significantly less susceptible. Device impedance decreased (current increased) after every failure. Such a failure mode may lead to cascading failures, as the damaged MOSFET may allow excessive current to flow through other circuitry. Preliminary assessments on a MOSFET subjected to 20-stroke pin-injection testing demonstrate that Breakdown Voltage, Leakage Current and Threshold Voltage characteristics show damage, while the device continues to meet manufacturer performance specifications. The purpose of this research is to develop validated tools, technologies, and techniques for automated detection, diagnosis and prognosis that enable mitigation of adverse events during flight, such as from lightning transients; and to understand the interplay between lightning-induced surges and aging (i.e. humidity, vibration thermal stress, etc.) on component degradation.

Ely, Jay J.↗