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At least 37 records · Page 2

Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management

Aircraft gas-turbine engine data is available from a variety of sources, including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data fusion is the integration of data or information from multiple sources for the achievement of improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/ information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This report describes a basic PHM data fusion architecture being developed in alignment with the NASA C-17 PHM Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center, NASA Dryden Flight Research Center, and Pratt & Whitney have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion, as it applies to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This report will provide a chronology and summary of the work accomplished under this research contract.

Volponi, Al↗

High resolution X-ray optics for astronomical and laboratory sources

In recent years X-ray telescopes have been used successfully for high resolution observations of astronomical objects, in particular the solar corona. At the present time X-ray microscopes are being developed for diagnostics of laser and electron beam induced fusion plasmas. This paper describes both types of imaging systems using as examples the AS&E X-ray telescope on Skylab and a 10X microscope being built for Los Alamos Scientific Laboratories. The designs, manufacturing tolerances, fabrication, testing, and performance are discussed. Steps for further development in both imaging areas are identified.

Silk, J. K.↗

Dynamic and Structural Gas Turbine Engine Modeling

Model the interactions between the structural dynamics and the performance dynamics of a gas turbine engine. Generally these two aspects are considered separate, unrelated phenomena and are studied independently. For diagnostic purposes, it is desirable to bring together as much information as possible, and that involves understanding how performance is affected by structural dynamics (if it is) and vice versa. This can involve the relationship between thrust response and the excitation of structural modes, for instance. The job will involve investigating and characterizing these dynamical relationships, generating a model that incorporates them, and suggesting and/or developing diagnostic and prognostic techniques that can be incorporated in a data fusion system. If no coupling is found, at the least a vibration model should be generated that can be used for diagnostics and prognostics related to blade loss, for instance.

Turso, James A.↗

Monitoring System for Storm Readiness and Recovery of Test Facilities: Integrated System Health Management (ISHM) Approach

Severe weather events are likely occurrences on the Mississippi Gulf Coast. It is important to rapidly diagnose and mitigate the effects of storms on Stennis Space Center's rocket engine test complex to avoid delays to critical test article programs, reduce costs, and maintain safety. An Integrated Systems Health Management (ISHM) approach and technologies are employed to integrate environmental (weather) monitoring, structural modeling, and the suite of available facility instrumentation to provide information for readiness before storms, rapid initial damage assessment to guide mitigation planning, and then support on-going assurance as repairs are effected and finally support recertification. The system is denominated Katrina Storm Monitoring System (KStorMS). Integrated Systems Health Management (ISHM) describes a comprehensive set of capabilities that provide insight into the behavior the health of a system. Knowing the status of a system allows decision makers to effectively plan and execute their mission. For example, early insight into component degradation and impending failures provides more time to develop work around strategies and more effectively plan for maintenance. Failures of system elements generally occur over time. Information extracted from sensor data, combined with system-wide knowledge bases and methods for information extraction and fusion, inference, and decision making, can be used to detect incipient failures. If failures do occur, it is critical to detect and isolate them, and suggest an appropriate course of action. ISHM enables determining the condition (health) of every element in a complex system-of-systems or SoS (detect anomalies, diagnose causes, predict future anomalies), and provide data, information, and knowledge (DIaK) to control systems for safe and effective operation. ISHM capability is achieved by using a wide range of technologies that enable anomaly detection, diagnostics, prognostics, and advise for control: (1) anomaly detection algorithms and strategies, (2) fusion of DIaK for anomaly detection (model-based, numerical, statistical, empirical, expert-based, qualitative, etc.), (3) diagnostics/prognostics strategies and methods, (4) user interface, (5) advanced control strategies, (6) integration architectures/frameworks, (7) embedding of intelligence. Many of these technologies are mature, and they are being used in the KStorMS. The paper will describe the design, implementation, and operation of the KStorMS; and discuss further evolution to support other needs such as condition-based maintenance (CBM).

Figueroa, Fernando↗

Spiral-Bevel-Gear Damage Detected Using Decision Fusion Analysis

Helicopter transmission integrity is critical to helicopter safety because helicopters depend on the power train for propulsion, lift, and flight maneuvering. To detect impending transmission failures, the ideal diagnostic tools used in the health-monitoring system would provide real-time health monitoring of the transmission, demonstrate a high level of reliable detection to minimize false alarms, and provide end users with clear information on the health of the system without requiring them to interpret large amounts of sensor data. A diagnostic tool for detecting damage to spiral bevel gears was developed. (Spiral bevel gears are used in helicopter transmissions to transfer power between nonparallel intersecting shafts.) Data fusion was used to integrate two different monitoring technologies, oil debris analysis and vibration, into a health-monitoring system for detecting surface fatigue pitting damage on the gears.

Dempsey, Paula J.↗

Investigation of Data Fusion Applied to Health Monitoring of Wind Turbine Drive train Components

The research described was performed on diagnostic tools used to detect damage to dynamic mechanical components in a wind turbine gearbox. Different monitoring technologies were evaluated by collecting vibration and oil debris data from tests performed on a "healthy" gearbox and a damaged gearbox in a dynamometer test stand located at the National Renewable Energy Laboratory. The damaged gearbox tested was removed from the field after experiencing component damage due to two losses of oil events and was retested under controlled conditions in the dynamometer test stand. Preliminary results indicate oil debris and vibration can be integrated to assess the health of the wind turbine gearbox.

Dempsey, Paula J.↗

A Comparison of Vibration and Oil Debris Gear Damage Detection Methods Applied to Pitting Damage

Helicopter Health Usage Monitoring Systems (HUMS) must provide reliable, real-time performance monitoring of helicopter operating parameters to prevent damage of flight critical components. Helicopter transmission diagnostics are an important part of a helicopter HUMS. In order to improve the reliability of transmission diagnostics, many researchers propose combining two technologies, vibration and oil monitoring, using data fusion and intelligent systems. Some benefits of combining multiple sensors to make decisions include improved detection capabilities and increased probability the event is detected. However, if the sensors are inaccurate, or the features extracted from the sensors are poor predictors of transmission health, integration of these sensors will decrease the accuracy of damage prediction. For this reason, one must verify the individual integrity of vibration and oil analysis methods prior to integrating the two technologies. This research focuses on comparing the capability of two vibration algorithms, FM4 and NA4, and a commercially available on-line oil debris monitor to detect pitting damage on spur gears in the NASA Glenn Research Center Spur Gear Fatigue Test Rig. Results from this research indicate that the rate of change of debris mass measured by the oil debris monitor is comparable to the vibration algorithms in detecting gear pitting damage.

Dempsey, Paula J.↗

Studies of Thermophysical Properties of Metals and Semiconductors by Containerless Processing Under Microgravity

Electromagnetic levitation under microgravity provides unique opportunities for the investigation of liquid metals, alloys and semiconductors, both above and below their melting temperatures, with minimized disturbances of the sample under investigation. The opportunity to perform such experiments will soon be available on the ISS with the EML payload which is currently being integrated. With its high-performance diagnostics systems EML allows to measure various physical properties such as heat capacity, enthalpy of fusion, viscosity, surface tension, thermal expansion coefficient, and electrical conductivity. In studies of nucleation and solidification phenomena the nucleation kinetics, phase selection, and solidification velocity can be determined. Advanced measurement capabilities currently being studied include the measurement and control of the residual oxygen content of the process atmosphere and a complementary inductive technique to measure thermophysical properties.

Seidel, A.↗

A Summary of the NASA Fusion Propulsion Workshop 2000

A NASA Fusion Propulsion Workshop was held on Nov. 8 and 9, 2000 at Marshall Space Flight Center (MSFC) in Huntsville, Alabama. A total of 43 papers were presented at the Workshop orally or by posters, covering a broad spectrum of issues related to applying fusion to propulsion. The status of fusion research was reported at the Workshop showing the outstanding scientific research that has been accomplished worldwide in the fusion energy research program. The international fusion research community has demonstrated the scientific principles of fusion creating plasmas with conditions for fusion burn with a gain of order unity: 0.25 in Princeton TFTR, 0.65 in the Joint European Torus, and a Q-equivalent of 1.25 in Japan's JT-60. This research has developed an impressive range of physics and technological capabilities that may be applied effectively to the research of possibly new propulsion-oriented fusion schemes. The pertinent physics capabilities include the plasma computational tools, the experimental plasma facilities, the diagnostics techniques, and the theoretical understanding. The enabling technologies include the various plasma heating, acceleration, and the pulsed power technologies.

Thio, Y. C. Francis↗

Integrating Oil Debris and Vibration Measurements for Intelligent Machine Health Monitoring

A diagnostic tool for detecting damage to gears was developed. Two different measurement technologies, oil debris analysis and vibration were integrated into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual measurement technologies. This diagnostic tool was developed and evaluated experimentally by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spur Gear Fatigue Rig. An oil debris sensor and the two vibration algorithms were adapted as the diagnostic tools. An inductance type oil debris sensor was selected for the oil analysis measurement technology. Gear damage data for this type of sensor was limited to data collected in the NASA Glenn test rigs. For this reason, this analysis included development of a parameter for detecting gear pitting damage using this type of sensor. The vibration data was used to calculate two previously available gear vibration diagnostic algorithms. The two vibration algorithms were selected based on their maturity and published success in detecting damage to gears. Oil debris and vibration features were then developed using fuzzy logic analysis techniques, then input into a multi sensor data fusion process. Results show combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spur gears. As a result of this research, this new diagnostic tool has significantly improved detection of gear damage in the NASA Glenn Spur Gear Fatigue Rigs. This research also resulted in several other findings that will improve the development of future health monitoring systems. Oil debris analysis was found to be more reliable than vibration analysis for detecting pitting fatigue failure of gears and is capable of indicating damage progression. Also, some vibration algorithms are as sensitive to operational effects as they are to damage. Another finding was that clear threshold limits must be established for diagnostic tools. Based on additional experimental data obtained from the NASA Glenn Spiral Bevel Gear Fatigue Rig, the methodology developed in this study can be successfully implemented on other geared systems.

Dempsey, Paula J.↗

Neural network application to comprehensive engine diagnostics

We have previously reported on the use of neural networks for detection and identification of faults in complex microprocessor controlled powertrain systems. The data analyzed in those studies consisted of the full spectrum of signals passing between the engine and the real-time microprocessor controller. The specific task of the classification system was to classify system operation as nominal or abnormal and to identify the fault present. The primary concern in earlier work was the identification of faults, in sensors or actuators in the powertrain system as it was exercised over its full operating range. The use of data from a variety of sources, each contributing some potentially useful information to the classification task, is commonly referred to as sensor fusion and typifies the type of problems successfully addressed using neural networks. In this work we explore the application of neural networks to a different diagnostic problem, the diagnosis of faults in newly manufactured engines and the utility of neural networks for process control.

Marko, Kenneth A.↗

SUMMA hot-ion plasma heating research at NASA Lewis Research Center

The SUMMA superconducting magnetic mirror facility and the associated hot-ion plasma research were described. SUMMA is characterized by intense magnetic fields and a large-diameter working bore (41 cm diameter) with room-temperature access. The goal of the plasma research program is to produce steady-state plasmas of fusion reactor densities and temperatures (but not confinement times). The program includes electrode development to produce a hot, dense, large-volume, steady-state plasma and diagnostics development to document the plasma properties. SUMMA and its hot-ion plasma are ideally suited to develop advanced plasma diagnostics methods. Two such methods whose requirements are well matched to SUMMA are: (1) heavy ion beam probing to measure plasma space potential; and (2) submillimeter wavelength laser Thomson scattering to measure local ion temperature.

Reinmann, J. J.↗

SUMMA hot-ion plasma heating research at NASA Lewis Research Center

This report describes the SUMMA superconducting magnetic mirror facility at the NASA Lewis Research Center and the hot-ion plasma research conducted therein. SUMMA is characterized by intense magnetic fields (designed for 8.6 T at the mirrors) and a large-diameter working bore (41 cm diameter) with room-temperature access. The goal of the plasma research program is to produce steady-state plasmas of fusion reactor densities and temperatures (but not confinement times). The program includes electrode development to produce a hot, dense, large-volume, steady-state plasma and diagnostics development to document the plasma properties. SUMMA and its hot-ion plasma are ideally suited to develop advanced plasma diagnostics methods. Two such methods whose requirements are well matched to SUMMA are: (1) heavy ion beam probing to measure plasma space potential, and (2) submillimeter wavelength laser Thomson scattering to measure local ion temperature. Two NASA University Grants were established to identify major requirements for developing these two diagnostic techniques in SUMMA.

Reinmann, J. J.↗

NASA Tech Briefs, January 2012

Contents of this issue are: (1) Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments (2) Handheld Universal Diagnostic Sensor (3) Large-Area Vacuum Ultraviolet Sensors (4) Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures (5) Health-Enabled Smart Sensor Fusion Technology (6) Extended-Range Passive RFID and Sensor Tags (7) Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks (8) Self-Healing, Inflatable, Rigidizable Shelter (9) Improvements in Cold-Plate Fabrication (10) Technique for Radiometer and Antenna Array Calibration - TRAAC (11) Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment (12) Programmable Digital Controller (13) Use of CCSDS Packets Over SpaceWire to Control Hardware (14) Key Decision Record Creation and Approval Module (15) Enhanced Graphics for Extended Scale Range (16) Debris Examination Using Ballistic and Radar Integrated Software (17) Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) (18) Integration Manager (19) Eclipse-Free-Time Assessment Tool for IRIS (20) Automated and Manual Rocket Crater Measurement Software (21) MATLAB Stability and Control Toolbox Trim and Static Stability Module (22) Patched Conic Trajectory Code (23) Ring Image Analyzer (24) SureTrak Probability of Impact Display (25) Implementation of a Non-Metallic Barrier in an Electric Motor (26) Multi-Mission Radioisotope Thermoelectric Generator Heat Exchangers for the Mars Science Laboratory Rover (27) Uniform Dust Distributor for Testing Radiative Emittance of Dust-Coated Surfaces (28) MicroProbe Small Unmanned Aerial System (29) Highly Stable and Active Catalyst for Sabatier Reactions (30) Better Proton-Conducting Polymers for Fuel-Cell Membranes (31) CCD Camera Lens Interface for Real-Time Theodolite Alignment (32) Peregrine 100-km Sounding Rocket Project (33) SOFIA Closed- and Open-Door Aerodynamic Analyses (34) Sonic Thermometer for High-Altitude Balloons (35) Near-Infrared Photon-Counting Camera for High-Sensitivity Observations (36) Integrated Optics Achromatic Nuller for Stellar Interferometry (37) High-Speed Digital Interferometry (38) Ultra-Miniature Lidar Scanner for Launch Range Data Collection (39) Shape and Color Features for Object Recognition Search (40) Explanation Capabilities for Behavior-Based Robot Control (41) A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks (42) Quality Control Method for a Micro-Nano-Channel Microfabricated Device (43) Corner-Cube Retroreflector Instrument for Advanced Lunar Laser Ranging (44) Electrospray Collection of Lunar Dust (45) Fabrication of a Kilopixel Array of Superconducting Microcalorimeters with Microstripline Wiring Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators (46) Coherent Detector for Near-Angle Scattering and Polarization Characterization of Telescope Mirror Coatings

Source record↗

The Diagnostics of the External Plasma for the Plasma Rocket

The plasma rocket is located at NASA Johnson Space Center. To produce a thrust in space. an inert gas is ionized into a plasma and heated in the linear section of a tokamak fusion device to 1 x 10(exp 4) - 1.16 x 10(exp 6)K(p= 10(exp 10) - 10(exp 14)/cu cm ). The magnetic field used to contain the plasma has a magnitude of 2 - 10k Gauss. The plasma plume has a variable thrust and specific impulse. A high temperature retarding potential analyzer (RPA) is being developed to characterize the plasma in the plume and at the edge of the magnetically contained plasma. The RPA measures the energy and density of ions or electrons entering into its solid angle of collection. An oscilloscope displays the ion flux versus the collected current. All measurements are made relative to the facility ground. A RPA is being developed in a process which involves the investigation of several prototypes. The first prototype has been tested on a thermal plasma. The knowledge gained from its development and testing were applied to the development of a RPA for collimated plasma. The prototypes consist of four equally spaced grids and an ion collector. The outermost grid is a ground. The second grid acts as a bias to repel electrons. The third is a variable v voltage ion suppressor. Grid four (inner grid) acts to repel secondary electrons, being biased equal to the first. Knowledge gained during these two stages are being applied to the development of a high temperature RPA Testing of this device involves the determination of its output parameters. sensitivity, and responses to a wide range of energies and densities. Each grid will be tested individually by changing only its voltage and observing the output from the RPA. To verify that the RPA is providing proper output. it is compared to the output from a Langmuir or Faraday probe.

Karr, Gerald R.↗

The NASA-JPL advanced propulsion program

The NASA Advanced Propulsion Concepts (APC) program at the Jet Propulsion Laboratory (JPL) consists of two main areas: The first involves cooperative modeling and research activities between JPL and various universities and industry; the second involves research at universities and industry that is directly supported by JPL. The cooperative research program consists of mission studies, research and development of ion engine technology using C-60 (Buckminsterfullerene) propellant, and research and development of lithium-propellant Lorentz-force accelerator (LFA) engine technology. The university/industry- supported research includes research (modeling and proof-of-concept experiments) in advanced, long-life electric propulsion, and in fusion propulsion. These propulsion concepts were selected primarily to cover a range of applications from near-term to far-term missions. For example, the long-lived pulsed-xenon thruster research that JPL is supporting at Princeton University addresses the near-term need for efficient, long-life attitude control and station-keeping propulsion for Earth-orbiting spacecraft. The C-60-propellant ion engine has the potential for good efficiency in a relatively low specific impulse (Isp) range (10,000 - 30,000 m/s) that is optimum for relatively fast (less than 100 day) cis-lunar (LEO/GEO/Lunar) missions employing near-term, high-specific mass electric propulsion vehicles. Research and modeling on the C-60-ion engine are currently being performed by JPL (engine demonstration), Caltech (C-60 properties), MIT (plume modeling), and USC (diagnostics). The Li-propellant LFA engine also has good efficiency in the modest Isp range (40,000 - 50,000 m/s) that is optimum for near-to-mid-term megawatt-class solar- and nuclear-electric propulsion vehicles used for Mars missions transporting cargo (in support of a piloted mission). Research and modeling on the Li-LFA engine are currently being performed by JPL (cathode development), Moscow Aviation Institute (engine testing), Thermacore (electrode development), as well as at MIT (plume modeling), and USC (diagnostics). Also, the mission performance of a nuclear-electric propulsion (NEP) Li-LFA Mars cargo vehicle is being modeled by JPL (mission analysis; thruster and power processor modeling) and the Rocketdyne Energy Technology and Engineering Center (ETEC) (power system modeling). Finally, the fusion propulsion research activities that JPL is supporting at Pennsylvania State University (PSU) and at Lawrenceville Plasma Physics (LPP) are aimed at far-term fast (less than 100 day round trip) piloted Mars missions and, in the very far term, interstellar missions.

Frisbee, Robert H.↗

Engineering of beam direct conversion for a 120-kV, 1-MW ion beam

Practical systems for beam direct conversion are required to recover the energy from ion beams at high efficiency and at very high beam power densities in the environment of a high-power neutral-injection system. Such an experiment is now in progress using a 120-kV beam with a maximum total current of 20 A. After neutralization, the H(+) component to be recovered will have a power of approximately 1 MW. A system testing these concepts has been designed and tested at 15 kV, 2 kW in preparation for the full-power tests. The engineering problems involved in the full-power tests affect electron suppression, gas pumping, voltage holding, diagnostics, and measurement conditions. Planning for future experiments at higher power includes the use of cryopumping and electron suppression by a magnetic field rather than by an electrostatic field. Beam direct conversion for large fusion experiments and reactors will save millions of dollars in the cost of power supplies and electricity and will dispose of the charged beam under conditions that may not be possible by other techniques.

Barr, W. L.↗

Health-Enabled Smart Sensor Fusion Technology

A process was designed to fuse data from multiple sensors in order to make a more accurate estimation of the environment and overall health in an intelligent rocket test facility (IRTF), to provide reliable, high-confidence measurements for a variety of propulsion test articles. The object of the technology is to provide sensor fusion based on a distributed architecture. Specifically, the fusion technology is intended to succeed in providing health condition monitoring capability at the intelligent transceiver, such as RF signal strength, battery reading, computing resource monitoring, and sensor data reading. The technology also provides analytic and diagnostic intelligence at the intelligent transceiver, enhancing the IEEE 1451.x-based standard for sensor data management and distributions, as well as providing appropriate communications protocols to enable complex interactions to support timely and high-quality flow of information among the system elements.

Wang, Ray↗