Results for “diagnostics” — Page 2

NASA NTRS1990

Embedding CLIPS in a database-oriented diagnostic system

This paper describes the integration of C Language Production Systems (CLIPS) into a powerful portable maintenance aid (PMA) system used for flightline diagnostics. The current diagnostic target of the system is the Garrett GTCP85-180L, a gas turbine engine used as an Auxiliary Power Unit (APU) on some C-130 military transport aircraft. This project is a database oriented approach to a generic diagnostic system. CLIPS is used for 'many-to-many' pattern matching within the diagnostics process. Patterns are stored in database format, and CLIPS code is generated by a 'compilation' process on the database. Multiple CLIPS rule sets and working memories (in sequence) are supported and communication between the rule sets is achieved via the export and import commands. Work is continuing on using CLIPS in other portions of the diagnostic system and in re-implementing the diagnostic system in the Ada language.

Conway, Tim↗

NASA NTRS1996

Conversion-Integration of MSFC Nonlinear Signal Diagnostic Analysis Algorithms for Realtime Execution of MSFC's MPP Prototype System

NASA's advanced propulsion system Small Scale Magnetic Disturbances/Advanced Technology Development (SSME/ATD) has been undergoing extensive flight certification and developmental testing, which involves large numbers of health monitoring measurements. To enhance engine safety and reliability, detailed analysis and evaluation of the measurement signals are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce the risk of catastrophic system failures and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. During the development of SSME, ASRI participated in the research and development of several advanced non- linear signal diagnostic methods for health monitoring and failure prediction in turbomachinery components. However, due to the intensive computational requirement associated with such advanced analysis tasks, current SSME dynamic data analysis and diagnostic evaluation is performed off-line following flight or ground test with a typical diagnostic turnaround time of one to two days. The objective of MSFC's MPP Prototype System is to eliminate such 'diagnostic lag time' by achieving signal processing and analysis in real-time. Such an on-line diagnostic system can provide sufficient lead time to initiate corrective action and also to enable efficient scheduling of inspection, maintenance and repair activities. The major objective of this project was to convert and implement a number of advanced nonlinear diagnostic DSP algorithms in a format consistent with that required for integration into the Vanderbilt Multigraph Architecture (MGA) Model Based Programming environment. This effort will allow the real-time execution of these algorithms using the MSFC MPP Prototype System. ASRI has completed the software conversion and integration of a sequence of nonlinear signal analysis techniques specified in the SOW for real-time execution on MSFC's MPP Prototype. This report documents and summarizes the results of the contract tasks; provides the complete computer source code; including all FORTRAN/C Utilities; and all other utilities/supporting software libraries that are required for operation.

Jong, Jen-Yi↗

NASA NTRS2009

Systematic Benchmarking of Diagnostic Technologies for an Electrical Power System

Automated health management is a critical functionality for complex aerospace systems. A wide variety of diagnostic algorithms have been developed to address this technical challenge. Unfortunately, the lack of support to perform large-scale V&V (verification and validation) of diagnostic technologies continues to create barriers to effective development and deployment of such algorithms for aerospace vehicles. In this paper, we describe a formal framework developed for benchmarking of diagnostic technologies. The diagnosed system is the Advanced Diagnostics and Prognostics Testbed (ADAPT), a real-world electrical power system (EPS), developed and maintained at the NASA Ames Research Center. The benchmarking approach provides a systematic, empirical basis to the testing of diagnostic software and is used to provide performance assessment for different diagnostic algorithms.

Kurtoglu, Tolga↗

NASA NTRS2010

Spontaneous Raman Scattering Diagnostics: Applications in Practical Combustion Systems

In this chapter, the recent advancements and practical aspects of laser SRS diagnostics have been reviewed wi til regards to applications in practical combustion systems. Clearly, SRS represents a theoretically and experimentally mature diagnostic technology that has become an essential tool for multiscalar measurements in turbulent combustion at elevated pressures. Today, time-, space-, spectrally, and even polarization-resolved S RS diagnostics is at hand, with aid from recent innovations in theoretical and technological developments on electro-optical or electromechanical devices. Whilst a linear increase in SRS signals can be expected in high-pressure systems (this is perhaps one of the most important advantages for using SRS in high-pressure systems), there are practical (often severe) restrictions associated with pressurized vessels, due mainly to the limited degree of optical access. This narrows ti,e available choice of diagnostics that can be employed at any given time. Point-wise SRS diagnostics provides the highest accuracy on the chemical species and temperature measurements, and will continue to remain a vital approach for the study in such harsh environments. The practical design considerations and hands-on set-up guide for SRS diagnostics provided in this chapter are rarely presented elsewhere. Although the second-harmonic Nd:YAG pulsed laser (532 nm), combined with pulse-stretching optics or the recently introduced White Cell-based laser, seems to be the most favored excitation source of choice by the research community, UV excitation will undoubtedly continue to be used on many occasions, and especially in sooting flames. Detection methods may be divided into ICCD-based nanosecond-gate detection or a rotary-chopper electromechanical shutter-based CCD array detection, and the levels of background flame emission in individual cases would determine this critical design choice. Here, a process of Raman signal calibration based on ti,e crosstalk matrix formalism was explained step-by-step. As tI,is process may be very time-consuming and expensive, a well-planned experimental approach (01' building a transferable calibration database or library (at least with in a user's own facility over a series of different testing and runs) is vitally important. Hands on advice on the design and construction of flow control systems for high pressure burner facilities were also presented.

Kojima, Jun↗

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 NTRS2016

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.

Diagnosis↗

NASA NTRS2021

A Comparison of Rest-frame Ultraviolet and Optical Emission-Line Diagnostics in the Lensed Galaxy SDSS J1723+3411 at Redshift z = 1.3293

For the extremely bright lensed galaxy SDSS J1723+3411 at z = 1.3293, we analyze spatially integrated MMT, Keck, and Hubble Space Telescope spectra that fully cover the rest-frame wavelength range of 1400 ̊A to 7200 ̊A. We also analyze near-IR spectra from Gemini that cover Hαfor a portion of the lensed arc. We report fluxes for 42 detected emission lines, and upper limits for an additional22. This galaxy has extreme emission line ratios and high equivalent widths that are characteristic of extreme emission-line galaxies. We compute strong emission line diagnostics from both the rest-frame optical and rest-frame ultraviolet (UV), to constrain physical conditions and test the spectral diagnostics themselves. We tightly determine the nebular physical conditions using the most reliable diagnostics, and then compare to results from other diagnostics. We find disappointing performance from the UV–only diagnostics: they either are unable to measure the metallicity or dramatically under-estimate it; they over-estimate the pressure; and the UV diagnostic of ionization parameter has a strong metallicity dependence in this regime. Based on these results, we suggest that upcoming James Webb Space Telescope(JWST) spectroscopic surveys of galaxies in the reionization epoch should invest the additional integration time to capture the optical [O II] and [O III] emission lines, and not rely solely on the rest-frame UV emission lines. We make available the spectra; they represent one of the highest-quality emission line spectral atlases of star-forming galaxy available beyond the local universe, and will aid planning observations with JWST.

galaxies↗

NASA NTRS1993

Qualitative model-based diagnostics for rocket systems

A diagnostic software package is currently being developed at NASA LeRC that utilizes qualitative model-based reasoning techniques. These techniques can provide diagnostic information about the operational condition of the modeled rocket engine system or subsystem. The diagnostic package combines a qualitative model solver with a constraint suspension algorithm. The constraint suspension algorithm directs the solver's operation to provide valuable fault isolation information about the modeled system. A qualitative model of the Space Shuttle Main Engine's oxidizer supply components was generated. A diagnostic application based on this qualitative model was constructed to process four test cases: three numerical simulations and one actual test firing. The diagnostic tool's fault isolation output compared favorably with the input fault condition.

Maul, William↗

NASA NTRS1993

Qualitative model-based diagnostics for rocket systems

A diagnostic software package is currently being developed at NASA LeRC that utilizes qualitative model-based reasoning techniques. These techniques can provide diagnostic information about the operational condition of the modeled rocket engine system or subsystem. The diagnostic package combines a qualitative model solver with a constraint suspension algorithm. The constraint suspension algorithm directs the solver's operation to provide valuable fault isolation information about the modeled system. A qualitative model of the Space Shuttle Main Engine's oxidizer supply components was generated. A diagnostic application based on this qualitative model was constructed to process four test cases: three numerical simulations and one actual test firing. The diagnostic tool's fault isolation output compared favorably with the input fault condition.

Maul, William↗

NASA NTRS1993

Laser diagnostics for small rockets

Two nonintrusive flowfield diagnostics based on spectrally-resolved elastic (Rayleigh) and inelastic (Raman) laser light scattering were developed for obtaining local flowfield measurements in low-thrust gaseous H2/O2 rocket engines. The objective is to provide an improved understanding of phenomena occurring in small chemical rockets in order to facilitate the development and validation of advanced computational fluid dynamics (CFD) models for analyzing engine performance. The laser Raman scattering diagnostic was developed to measure major polyatomic species number densities and rotational temperatures in the high-density flowfield region extending from the injector through the chamber throat. Initial application of the Raman scattering diagnostic provided O2 number density and rotational temperature measurements in the exit plane of a low area-ratio nozzle and in the combustion chamber of a two-dimensional, optically-accessible rocket engine. In the low-density nozzle exit plane region where the Raman signal is too weak, a Doppler-resolved laser Rayleigh scattering diagnostic was developed to obtain axial and radial mean gas velocities, and in certain cases, H2O translational temperature and number density. The results from these measurements were compared with theoretical predictions from the RPLUS CFD code for analyzing rocket engine performance. Initial conclusions indicate that a detailed and rigorous modeling of the injector is required in order to make direct comparisons between laser diagnostic measurements and CFD predictions at the local level.

Zupanc, Frank J.↗

NASA NTRS1995

Diagnostics in Japan's microgravity experiments

The achievement of the combustion research under microgravity depends substantially on the availability of diagnostic systems. The non-intrusive diagnostic systems are potentially applicable for providing the accurate, realistic and detailed information on momentum, mass and energy transport, complex gas phase chemistry, and phase change in the combustion field under microgravity. The non-intrusive nature of optical instruments is essential to the measurement of combustion process under microgravity which is very nervous to any perturbation. However, the implementation of the non-intrusive combustion diagnostic systems under microgravity is accompanied by several constraints. Usually, a very limited space is only available for constructing a highly sophisticated system which is so sensitive that it is easily affected by the magnitude of the gravitational force, vibration and heterogeneous field of temperature and density of the environments. The system should be properly adjusted prior to the experiment. Generally, it is quite difficult to tune the instruments during measurements. The programmed sequence of operation should also be provided. Extensive effort has been toward the development of non-intrusive diagnostic systems available for the combustion experiments under microgravity. This paper aims to describe the current art and the future strategy on the non-intrusive diagnostic systems potentially applicable to the combustion experiments under microgravity in Japan.

Kadota, Toshikazu↗

NASA NTRS1995

Development of advanced diagnostics for characterization of burning droplets in microgravity

Diagnostic techniques currently used for microgravity research are generally not as advanced as those used in earth based gravity experiments. Diagnostic techniques for measuring the instantaneous radial temperature profile (or temperature gradients) within the burning droplet do not exist. Over the past few years, Aerometrics has been researching and developing a rainbow thermometric technique for measuring the droplet temperatures of burning droplets. This technique has recently been integrated with the phase Doppler interferometric technique to yield a diagnostic instrument that can be used to simultaneously measure the size, velocity, and temperature of burning droplets in complex spray flames. Also, the rainbow thermometric technique has been recently integrated with a point-diffraction interferometric technique for measuring the instantaneous gas phase temperature field surrounding a burning droplet. These research programs, apart from being very successful, have also helped us identify other innovative techniques for the characterization of burning droplets. For example, new techniques have been identified for measuring the instantaneous regression rate of burning droplets. Also, there is the possibility of extracting the instantaneous radial temperature distribution or the temperature gradients within a droplet during transient heating. What is important is that these diagnostic techniques have the potential for making use of inexpensive, light-weight, and rugged devices such as diode lasers and linear CCD arrays. As a result, they can be easily packaged for incorporation into microgravity drop-test and flight-test facilities. Furthermore, with the use of linear CCD arrays, data rates as high as 10-100 kHz can be easily achieved. This data rate is orders of magnitude higher than what is currently achievable. In this research and development program, a compact and rugged diagnostic system will be developed that can be used to measure instantaneous fuel droplet diameter, droplet regression rate, and the droplet internal temperature profiles or gradients at very high data rates in microgravity experiments.

Sankar, Subramanian↗

NASA NTRS1996

Rayleigh Scattering Diagnostics Workshop

The Rayleigh Scattering Diagnostics Workshop was held July 25-26, 1995 at the NASA Lewis Research Center in Cleveland, Ohio. The purpose of the workshop was to foster timely exchange of information and expertise acquired by researchers and users of laser based Rayleigh scattering diagnostics for aerospace flow facilities and other applications. This Conference Publication includes the 12 technical presentations and transcriptions of the two panel discussions. The first panel was made up of 'users' of optical diagnostics, mainly in aerospace test facilities, and its purpose was to assess areas of potential applications of Rayleigh scattering diagnostics. The second panel was made up of active researchers in Rayleigh scattering diagnostics, and its purpose was to discuss the direction of future work.

Seasholtz, Richard↗

NASA NTRS1999

A Compact, Tunable Near-UV Source for Quantitative Microgravity Combustion Diagnostics

There is a need for improved optical diagnostic methods for use in microgravity combustion research. Spectroscopic methods with fast time response that can provide absolute concentrations and concentration profiles of important chemical species in flames are needed to facilitate the understanding of combustion kinetics in microgravity. Although a variety of sophisticated laser-based diagnostics (such as planar laser induced fluorescence, degenerate four wave mixing and coherent Raman methods) have been applied to the study of combustion in laboratory flames, the instrumentation associated with these methods is not well suited to microgravity drop tower or space station platforms. Important attributes of diagnostic systems for such applications include compact size, low power consumption, ruggedness, and reliability. We describe a diode laser-based near-UV source designed with the constraints of microgravity research in mind. Coherent light near 420 nm is generated by frequency doubling in a nonlinear crystal. This light source is single mode with a very narrow bandwidth suitable for gas phase diagnostics, can be tuned over several 1/cm and can be wavelength modulated at up to MHz frequencies. We demonstrate the usefulness of this source for combustion diagnostics by measuring CH radical concentration profiles in an atmospheric pressure laboratory flame. The radical concentrations are measured using wavelength modulation spectroscopy (WMS) to obtain the line-of-sight integrated absorption for different paths through the flame. Laser induced fluorescence (LIF) measurements are also demonstrated with this instrument, showing the feasibility of simultaneous WMS absorption and LIF measurements with the same light source. LIF detection perpendicular to the laser beam can be used to map relative species densities along the line-of-sight while the integrated absorption available through WMS provides a mathematical constraint on the extraction of quantitative information from the LIF data. Combining absorption with LIF - especially if the measurements are made simultaneously with the same excitation beam - may allow elimination of geometrical factors and effects of intensity fluctuations (common difficulties with the analysis of LIF data) from the analysis.

Peterson, K. A.↗

NASA NTRS2004

Development of an Information Fusion System for Engine Diagnostics and Health Management

Aircraft gas-turbine engine data are 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, to achieve 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 paper describes a basic PHM Data Fusion architecture being developed in alignment with the NASA C17 Propulsion Health Management (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 (GRC), NASA Dryden Flight Research Center (DFRC) and Pratt & Whitney (P&W) have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion as applied 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 paper will provide a broad overview of this work, discuss some of the methodologies employed and give some illustrative examples.

Volponi, Allan J.↗

NASA NTRS2004

Advanced Optical Diagnostic Methods for Describing Fuel Injection and Combustion Flowfield Phenomena

Over the past decade advanced optical diagnostic techniques have evolved and matured to a point where they are now widely applied in the interrogation of high pressure combusting flows. At NASA Glenn Research Center (GRC), imaging techniques have been used successfully in on-going work to develop the next generation of commercial aircraft gas turbine combustors. This work has centered on providing a means by which researchers and designers can obtain direct visual observation and measurements of the fuel injection/mixing/combustion processes and combustor flowfield in two- and three-dimensional views at actual operational conditions. Obtaining a thorough understanding of the chemical and physical processes at the extreme operating conditions of the next generation of combustors is critical to reducing emissions and increasing fuel efficiency. To accomplish this and other tasks, the diagnostic team at GRC has designed and constructed optically accessible, high pressurer high temperature flame tubes and sectar rigs capable of optically probing the 20-60 atm flowfields of these aero-combustors. Among the techniques employed at GRC are planar laser-induced fluorescence (PLIF) for imaging molecular species as well as liquid and gaseous fuel; planar light scattering (PLS) for imaging fuel sprays and droplets; and spontaneous Raman scattering for species and temperature measurement. Using these techniques, optical measurements never before possible have been made in the actual environments of liquid fueled gas turbines. 2-D mapping of such parameters as species (e.g. OH-, NO and kerosene-based jet fuel) distribution, injector spray angle, and fuel/air distribution are just some of the measurements that are now routinely made. Optical imaging has also provided prompt feedback to researchers regarding the effects of changes in the fuel injector configuration on both combustor performance and flowfield character. Several injector design modifications and improvements have resulted from this feedback. Alternate diagnostic methods are constantly being evaluated as to their suitability as a diagnostic tool in these environments. A new method currently under examination is background oriented Schlieren (BOS) for examining the fuel/air mixing processes. While ratioing the Stokes and anti-Stokes nitrogen lines obtained from spontaneous Raman is being refined for temperature measurement. While the primary focus of the GRC diagnostic work remains optical species measurement and flow stream characterization, an increased emphasis has been placed on our involvement in flame code validation efforts. A functional combustor code should shorten and streamline future combustor design. Quantitative measurements of flow parameters such as temperature, species concentration, drop size and velocity using such methods as Raman and phase Doppler anemometry will provide data necessary in this effort.

Locke, Randy J.↗

NASA NTRS2005

A Review of Diagnostic Techniques for ISHM Applications

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Patterson-Hine, Ann↗