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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Application of visible linear array technology to earth observation sensors

The present paper identifies the systems engineering aspects of applying solid-state technology to earth observations applications being traditionally performed by point (or multiple-point) detector line scanned mechanisms. It is shown that the translation from a basically serial data flow point-detector mechanically-scanned sensor to a solid state highly parallel linear-array pushbroom sensor results in minimizing mechanical complexity and maximizing electronics complexity, with increased demands upon optical performance in some applications. Technical aspects relevant to highly parallel photodiode linear-array pushbroom applications are discussed. Examples of systems engineering applications are provided.

Noll, R. E.↗
NASA NTRS2004

Requirements to Design to Code: Towards a Fully Formal Approach to Automatic Code Generation

A general-purpose method to mechanically transform system requirements into a provably equivalent model has yet to appear. Such a method represents a necessary step toward high-dependability system engineering for numerous possible application domains, including sensor networks and autonomous systems. Currently available tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The gap that current tools and methods leave unfilled is that their formal models cannot be proven to be equivalent to the system requirements as originated by the customer. For the classes of systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or in other appropriate graphical notations) into a provably equivalent formal model that can be used as the basis for code generation and other transformations.

Hinchey, Michael G.↗
NASA NTRS2015

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗
NASA NTRS2015

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗
NASA NTRS1990

Annual Health Monitoring Conference for Space Propulsion Systems, 2nd, Cincinnati, OH, Nov. 14, 15, 1990, Proceedings

This conference discusses health management systems for liquid rocket engines, signal processing of spectroscopic data for engine diagnostic applications, real-time diagnostics of the reusable rocket engine using on-line system identification, and nonlinear parameter estimation for rocket engine health monitoring. Plume diagnostics are considered including discussion on preliminary plume diagnostics on the SSME using video digitization techniques and baseline plume emmissions. The development of a Fabry-Perot Interferometer for rocket engine plumes is also considered. The topic of computational modeling is also discussed, addressing such topics as probabalistic dynamics of material loss in the SSME turbomachinery, state-variable modelling of fluid-dynamics processes, and a model for the SSME high pressure oxidizer turbopump shaft seal system. A discussion of sensor development includes the topics of sensor development for the rocket engine condition monitoring system and the heat flux measurements in SSME turbine blade tester.

Source record↗
NASA NTRS2001

A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter

Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems. We are exploring the use of one of these techniques, which utilizes multi-signal modeling and the TEAMS-RT real-time diagnostic engine, on the UH-60 Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) flight research aircraft. We focus on the engine and transmission systems, and acquire sensor data across the 1553 bus as well as by direct analog-to-digital conversion from sensors to the QHuMS (Qualtech health and usage monitoring system) computer. The QHuMS computer uses commercially available components and is rack-mounted in the RASCAL facility. A multi-signal model of the transmission and engine subsystems enables studies of system testability and analysis of the degree of fault isolation available with various instrumentation suites. The model and examples of these analyses will be described and the data architectures enumerated. Flight tests of this system will validate the data architecture and provide real-time flight profiles to be further analyzed in the laboratory.

Patterson-Hine, Ann↗
NASA NTRS1989

Reusable rocket engine turbopump health monitoring system, part 3

Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms.

Perry, John G.↗
NASA NTRS1988

Engine-Monitoring Algorithm

Allowances made for erroneous sensor readings. Algorithm developed to increase reliability of digital electronic control systems for aircraft turbine engines. Detects, isolates, and accommodates failures or errors in engine sensors. Generates engine-output estimates based on measurements of inputs and outputs and detects failures of input- and output-measuring sensors.

Merrill, Walter C.↗
NASA NTRS1982

Status of fiberoptics technology for propulsion control systems

Optical sensors and optically controlled actuators for use in airbreathing engine control systems are discussed. The environmental conditions in which the aircraft will operate require the fiberoptic cables and optical connectors to perform reliably at temperatures over the -55 C to 260 C range. The status of fiberoptics technology for operation in this environment is reviewed.

Baumbick, R. J.↗
NASA NTRS2003

Fracture Evaluation of In-Situ Sensors for High Temperature Applications

The feasibility of fabricating an in-situ crack sensor for real-time detection of surface cracks propagating in engine components was evaluated using a computational fracture mechanics model. The in-situ sensor system would be required to: (1) Be capable of sustaining normal function in a severe environment; (2) Transmit a signal if a detected crack in the component was above a predetermined length, but below a critical length that would lead to failure; (3) Act neutrally upon the overall performance of the engine system and not interfere with the engine maintenance operations. In this work, fracture mechanics methodologies are used to identify the requirements for an in-situ sensor system that could withstand the engine operating environment, foreign object damage, and minimally degrade engine performance. A computational fracture mechanics model was developed to evaluate the feasibility of fabricating an in-situ crack sensor for real-time damage propagation detection in engine components.

Forth, Scott C.↗
NASA NTRS2007

"Smart" Sensor Module

An assembly that contains a sensor, sensor-signal-conditioning circuitry, a sensor-readout analog-to-digital converter (ADC), data-storage circuitry, and a microprocessor that runs special-purpose software and communicates with one or more external computer(s) has been developed as a prototype of "smart" sensor modules for monitoring the integrity and functionality (the "health") of engineering systems. Although these modules are now being designed specifically for use on rocket-engine test stands, it is anticipated that they could also readily be designed to be incorporated into health-monitoring subsystems of such diverse engineering systems as spacecraft, aircraft, land vehicles, bridges, buildings, power plants, oilrigs, and defense installations. The figure is a simplified block diagram of the "smart" sensor module. The analog sensor readout signal is processed by the ADC, the digital output of which is fed to the microprocessor. By means of a standard RS-232 cable, the microprocessor is connected to a local personal computer (PC), from which software is downloaded into a randomaccess memory in the microprocessor. The local PC is also used to debug the software. Once the software is running, the local PC is disconnected and the module is controlled by, and all output data from the module are collected by, a remote PC via an Ethernet bus. Several smart sensor modules like this one could be connected to the same Ethernet bus and controlled by the single remote PC. The software running in the microprocessor includes driver programs for operation of the sensor, programs that implement self-assessment algorithms, programs that implement protocols for communication with the external computer( s), and programs that implement evolutionary methodologies to enable the module to improve its performance over time. The design of the module and of the health-monitoring system of which it is a part reflects the understanding that the main purpose of a health-monitoring system is to detect damage and, therefore, the health-monitoring system must be able to function effectively in the presence of damage and should be capable of distinguishing between damage to itself and damage to the system being monitored. A major benefit afforded by the self-assessment algorithms is that in the output of the module, the sensor data indicative of the health of the engineering system being monitored are coupled with a confidence factor that quantifies the degree of reliability of the data. Hence, the output includes information on the health of the sensor module itself in addition to information on the health of the engineering system being monitored.

Mahajan, Ajay↗
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 NTRS2008

Development of a Temperature Sensor for Jet Engine and Space Missions Environments

Electronic systems in aerospace and in space exploration missions are expected to encounter extreme temperatures and wide thermal swings. To address the needs for extreme temperature electronics, research efforts exist at the NASA Glenn Research Center (GRC) to develop and evaluate electronics for extreme temperature operations, and to establish their reliability under extreme temperature operation and thermal cycling; conditions that are typical of both the aerospace and space environments. These efforts are supported by the NASA Fundamental Aeronautics/Subsonic Fixed Wing Program and by the NASA Electronic Parts and Packaging (NEPP) Program. This work reports on the results obtained on the development of a temperature sensor geared for use in harsh environments.

Patterson, Richard L.↗
NASA NTRS1993

More About Detecting Sensor Failures In A Turbofan Engine

Advanced Detection, Isolation, and Accommodation (ADIA) algorithm helps digital electronic multivariable-control system of advanced turbofan engine cope with failures of sensors in real time. Algorithm includes four major elements: hard-sensor-failure detection-and-isolation logic, soft-sensor-failure detection-and-isolation logic, accommodation filter, and interface switch matrix.

Delaat, John C.↗
NASA NTRS1995

Clementine Engineering Experiments Program.

Spacecraft must survive and operate reliably in the space environment for long periods of time. Radiation, temperature variations, spacecraft charging, surface contamination, and micrometeoroids/space debris all present environmental challenges to spacecraft missions. The environmental issues associated with these effects require in-situ space experiments to properly quantify the environment and its effects. To obtain data on specific microelectronic and sensor systems in the space environment, several engineering experiments were developed for the Clementine spacecraft and the Clementine lunar transfer booster or Interstage Adapter Satellite (ISAS). These platforms allowed testing of advanced spacecraft microelectronic and sensor devices in a lunar transfer orbit that intersects Earth's radiation belts and debris environment and in interplanetary space where direct exposure to solar flares, Galactic Cosmic Rays, and micrometeoroids was possible. A suite of experiments was developed by the Naval Research Laboratory (NRL), the Jet Propulsion Laboratory (JPL), NASA Langley Research Center (LaRC), the Aerospace Corporation, and NASA Goddard Space Flight Center (GSFC) to investigate in detail specific radiation and environmental reliability issues. This paper presents an introduction to the issues being investigated, the instruments provided for the mission, and the rationale for the engineering program.

Spacecraft↗
NASA NTRS1980

Performance seeking controls

A performance logic algorithm (PSL) was developed to optimize the performance of propulsion systems for component and sensor degradations by monitoring the performance of the engine system and minimizing thrust specific fuel consumption (TSFC) while retaining a constant engine net thrust. Engine constraints such as surge margin, speed, pressure, and temperature are observed. The PSL algorithm was applied to the quiet, clean, short haul experimental engine. Engine control set points were modified for component degradations in order to restore the nominal net thrust. Results show convergence to the optimum value can be obtained within 60 to 90 seconds, which makes the program acceptable to on line operation with present state of the art minicomputers. Tests indicate that in most cases the PSL algorithm offers some improvement in thrust specific fuel consumption over the manual throttle.

Seldner, K.↗