SEARCH · Engineering Papers

Results for “Diagnostics”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

All sources NASA NTRS DOE OSTI

NASA NTRS2006

Hybrid Kalman Filter: A New Approach for Aircraft Engine In-Flight Diagnostics

In this paper, a uniquely structured Kalman filter is developed for its application to in-flight diagnostics of aircraft gas turbine engines. The Kalman filter is a hybrid of a nonlinear on-board engine model (OBEM) and piecewise linear models. The utilization of the nonlinear OBEM allows the reference health baseline of the in-flight diagnostic system to be updated to the degraded health condition of the engines through a relatively simple process. Through this health baseline update, the effectiveness of the in-flight diagnostic algorithm can be maintained as the health of the engine degrades over time. Another significant aspect of the hybrid Kalman filter methodology is its capability to take advantage of conventional linear and nonlinear Kalman filter approaches. Based on the hybrid Kalman filter, an in-flight fault detection system is developed, and its diagnostic capability is evaluated in a simulation environment. Through the evaluation, the suitability of the hybrid Kalman filter technique for aircraft engine in-flight diagnostics is demonstrated.

Kobayashi, Takahisa↗

NASA NTRS2008

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Sowers, T. Shane↗

NASA NTRS2008

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Sowers, T. Shane↗

NASA NTRS2010

An Integrated Architecture for On-Board Aircraft Engine Performance Trend Monitoring and Gas Path Fault Diagnostics

Aircraft engine performance trend monitoring and gas path fault diagnostics are closely related technologies that assist operators in managing the health of their gas turbine engine assets. Trend monitoring is the process of monitoring the gradual performance change that an aircraft engine will naturally incur over time due to turbomachinery deterioration, while gas path diagnostics is the process of detecting and isolating the occurrence of any faults impacting engine flow-path performance. Today, performance trend monitoring and gas path fault diagnostic functions are performed by a combination of on-board and off-board strategies. On-board engine control computers contain logic that monitors for anomalous engine operation in real-time. Off-board ground stations are used to conduct fleet-wide engine trend monitoring and fault diagnostics based on data collected from each engine each flight. Continuing advances in avionics are enabling the migration of portions of the ground-based functionality on-board, giving rise to more sophisticated on-board engine health management capabilities. This paper reviews the conventional engine performance trend monitoring and gas path fault diagnostic architecture commonly applied today, and presents a proposed enhanced on-board architecture for future applications. The enhanced architecture gains real-time access to an expanded quantity of engine parameters, and provides advanced on-board model-based estimation capabilities. The benefits of the enhanced architecture include the real-time continuous monitoring of engine health, the early diagnosis of fault conditions, and the estimation of unmeasured engine performance parameters. A future vision to advance the enhanced architecture is also presented and discussed

Simon, Donald L.↗

NASA NTRS2010

Application of Diagnostic Analysis Tools to the Ares I Thrust Vector Control System

The NASA Ares I Crew Launch Vehicle is being designed to support missions to the International Space Station (ISS), to the Moon, and beyond. The Ares I is undergoing design and development utilizing commercial-off-the-shelf tools and hardware when applicable, along with cutting edge launch technologies and state-of-the-art design and development. In support of the vehicle s design and development, the Ares Functional Fault Analysis group was tasked to develop an Ares Vehicle Diagnostic Model (AVDM) and to demonstrate the capability of that model to support failure-related analyses and design integration. One important component of the AVDM is the Upper Stage (US) Thrust Vector Control (TVC) diagnostic model-a representation of the failure space of the US TVC subsystem. This paper first presents an overview of the AVDM, its development approach, and the software used to implement the model and conduct diagnostic analysis. It then uses the US TVC diagnostic model to illustrate details of the development, implementation, analysis, and verification processes. Finally, the paper describes how the AVDM model can impact both design and ground operations, and how some of these impacts are being realized during discussions of US TVC diagnostic analyses with US TVC designers.

Maul, William A.↗

NASA NTRS2009

Benchmarking Diagnostic Algorithms on an Electrical Power System Testbed

Diagnostic algorithms (DAs) are key to enabling automated health management. These algorithms are designed to detect and isolate anomalies of either a component or the whole system based on observations received from sensors. In recent years a wide range of algorithms, both model-based and data-driven, have been developed to increase autonomy and improve system reliability and affordability. However, the lack of support to perform systematic benchmarking of these algorithms continues to create barriers for effective development and deployment of diagnostic technologies. In this paper, we present our efforts to benchmark a set of DAs on a common platform using a framework that was developed to evaluate and compare various performance metrics for diagnostic technologies. The diagnosed system is an electrical power system, namely the Advanced Diagnostics and Prognostics Testbed (ADAPT) developed and located at the NASA Ames Research Center. The paper presents the fundamentals of the benchmarking framework, the ADAPT system, description of faults and data sets, the metrics used for evaluation, and an in-depth analysis of benchmarking results obtained from testing ten diagnostic algorithms on the ADAPT electrical power system testbed.

Kurtoglu, Tolga↗

NASA NTRS2013

Aircraft Engine Gas Path Diagnostic Methods: Public Benchmarking Results

Recent technology reviews have identified the need for objective assessments of aircraft engine health management (EHM) technologies. To help address this issue, a gas path diagnostic benchmark problem has been created and made publicly available. This software tool, referred to as the Propulsion Diagnostic Method Evaluation Strategy (ProDiMES), has been constructed based on feedback provided by the aircraft EHM community. It provides a standard benchmark problem enabling users to develop, evaluate and compare diagnostic methods. This paper will present an overview of ProDiMES along with a description of four gas path diagnostic methods developed and applied to the problem. These methods, which include analytical and empirical diagnostic techniques, will be described and associated blind-test-case metric results will be presented and compared. Lessons learned along with recommendations for improving the public benchmarking processes will also be presented and discussed.

Simon, Donald L.↗

NASA NTRS2018

A Laser-Induced Fluorescence Diagnostic for HERMeS and High-Power Electric Propulsion

NASA is continuing the development of a 12.5-kW Hall thruster system, which is baselined in a phased exploration concept to expand human presence to cis-lunar space and eventually to Mars. The development team is transitioning knowledge gained from the testing of the government-built Technology Development Unit (TDU) to the contractor-built Engineering Development Unit (EDU). A new laser-induced fluorescence diagnostic that is compatible with the testing of engineering hardware was developed to obtain data for thruster model validation in the lowest background pressure achievable. Prior to performing the test on the EDU, the team performed a functional checkout test of this new diagnostic using the TDU. In addition to providing a checkout of the diagnostic, this test provided data that can be correlated to electron mobility for comparison to the EDU at a later date. A number of technical challenges related to large test facilities and interfacing with engineering hardware were overcome while implementing the new laser diagnostic system. The initial data set was in good agreement with prior optical and non-optical diagnostics data collected on the TDU thrusters. This data set also revealed the spatial origin of high angle ions that have been of concern for spacecraft integration.

Huang, Wensheng↗

NASA NTRS2018

A Laser-Induced Fluorescence Diagnostic for HERMeS and High-Power Electric Propulsion

Huang, Wensheng↗

NASA NTRSDate not supplied

SPIKE-Dx : A Low-Power High-Throughput Fault Diagnostics Tool using Spiking Neural Networks for Constrained Systems

Diagnostic systems are important for many aerospace systems, which are severely limited in available power, like cubesats or UAVs. Therefore, traditional diagnostics systems cannot be used due to their substantial footprint and constraints. In this paper, we present our very low power diagnostic tool SPIKE-DX to monitor critical systems with constrained computational and energy resources. This is made possible through spiking neural networks (SNNs), which are executable within optimized simulation environments and further implemented on on cutting-edge neuromorphic hardware. Based upon FMEA (Failure Mode and Effect Analysis) framework, Diagnostic Bayesian Networks (DBNs) can be constructed that provide powerful means for diagnostic reasoning. In this paper, we describe such DBNs and a method to automatically translate the DBN into highly structured networks of spiking neurons for execution in SPIKE-DX.

Spiking Neural Networks↗

NASA NTRS1979

Diagnostics of wear in aeronautical systems

The use of appropriate diagnostic tools for aircraft oil wetted components is reviewed, noting that it can reduce direct operating costs through reduced unscheduled maintenance, particularly in helicopter engine and transmission systems where bearing failures are a significant cost factor. Engine and transmission wear modes are described, and diagnostic methods for oil and wet particle analysis, the spectrometric oil analysis program, chip detectors, ferrography, in-line oil monitor and radioactive isotope tagging are discussed, noting that they are effective over a limited range of particle sizes but compliment each other if used in parallel. Fine filtration can potentially increase time between overhauls, but reduces the effectiveness of conventional oil monitoring techniques so that alternative diagnostic techniques must be used. It is concluded that the development of a diagnostic system should be parallel and integral with the development of a mechanical system.

Wedeven, L. D.↗

NASA NTRS1984

Combustion diagnostics by nonintrusive methods; Thermophysics Conference, 18th, Montreal, Canada, June 1-3, 1983, Selected Papers

The state of the art in coherent anti-Stokes Raman scattering (CARS) and laser-induced fluorescence (LIF) is outlined, and current diagnostic capabilities in particle and combustion diagnostics are demonstrated. The development and application of CARS to combustion systems is discussed, and the use of LIF for flow diagnostics is addressed. Nonintrusive particle diagnostics is treated, and a variety of nonintrusive techniques applied to combustion environments is considered.

Mccay, T. D.↗

NASA NTRS1987

An easy-to-use diagnostic system development shell

The Diagnostic System Development Shell (DSDS), an expert system development shell for diagnostic systems, is described. The major objective of building the DSDS is to create a very easy to use and friendly environment for knowledge engineers and end-users. The DSDS is written in OPS5 and CommonLisp. It runs on a VAX/VMS system. A set of domain independent, generalized rules is built in the DSDS, so the users need not be concerned about building the rules. The facts are explicitly represented in a unified format. A powerful check facility which helps the user to check the errors in the created knowledge bases is provided. A judgement facility and other useful facilities are also available. A diagnostic system based on the DSDS system is question driven and can call or be called by other knowledge based systems written in OPS5 and CommonLisp. A prototype diagnostic system for diagnosing a Philips constant potential X-ray system has been built using the DSDS.

Tsai, L. C.↗

NASA NTRS1988

Integrated diagnostics

Recently completed projects in which advanced diagnostic concepts were explored and/or demonstrated are summarized. The projects begin with the design of integrated diagnostics for the Army's new gas turbine engines, and advance to the application of integrated diagnostics to other aircraft subsystems. Finally, a recent project is discussed which ties together subsystem fault monitoring and diagnostics with a more complete picture of flight domain knowledge.

Hunthausen, Roger J.↗

NASA NTRS1988

A fault injection experiment using the AIRLAB Diagnostic Emulation Facility

The preparation for, conduct of, and results of a simulation based fault injection experiment conducted using the AIRLAB Diagnostic Emulation facilities is described. An objective of this experiment was to determine the effectiveness of the diagnostic self-test sequences used to uncover latent faults in a logic network providing the key fault tolerance features for a flight control computer. Another objective was to develop methods, tools, and techniques for conducting the experiment. More than 1600 faults were injected into a logic gate level model of the Data Communicator/Interstage (C/I). For each fault injected, diagnostic self-test sequences consisting of over 300 test vectors were supplied to the C/I model as inputs. For each test vector within a test sequence, the outputs from the C/I model were compared to the outputs of a fault free C/I. If the outputs differed, the fault was considered detectable for the given test vector. These results were then analyzed to determine the effectiveness of some test sequences. The results established coverage of selt-test diagnostics, identified areas in the C/I logic where the tests did not locate faults, and suggest fault latency reduction opportunities.

Baker, Robert↗

NASA NTRS1989

A self diagnostic system for piezoelectric sensors

A technique for determining the mounting conditions of a piezoelectric accelerometer is presented. This technique electrically stimulates the piezoelectric element in the 'diagnostic' frequency band measuring the electrical frequency response characteristics across a capacitive load impedance. The diagnostic frequency band is tipically much higher than the operating bandwidth of the accelerometer. The resonant frequencies of the accelerometer are included in the diagnostic band. By monitoring the shift in these resonant frequencies, via electrical stimulation techniques, certain diagnostic conditions including mounting conditions can be determined. Experimental data from a compression mode accelerometer is used to demonstrate this technique.

Atherton, William J.↗

NASA NTRS1992

Nonintrusive spectroscopic techniques for supersonic/hypersonic aerodynamics and combustion diagnostics

This paper presents an overview of the primary nonintrusive diagnostic techniques being developed by the NASA Langley Research Center to address the validation needs of Computational Fluid Dynamic (CFD) codes. The techniques include absorption in the UV and IR, Laser Induced Fluorescence, electron beam fluorescence, and a number of scattering techniques including Rayleigh, spontaneous Raman, and several coherent Raman spectroscopies. Most of the techniques are highly specialized, require complex data interpretation, and can satisfy only a few of the CFD needs. For these reasons, the evolving trend in flowfield diagnostics appears to favor a mode in which the diagnostic researcher, the experimental aerodynamicist, and the CFD community jointly define experiments based on the aeronautical requirements and on available diagnostic techniques.

Exton, R. J.↗

NASA NTRS1993

Small rocket flowfield diagnostic chambers

Instrumented and optically-accessible rocket chambers are being developed to be used for diagnostics of small rocket (less than 440 N thrust level) flowfields. These chambers are being tested to gather local fluid dynamic and thermodynamic flowfield data over a range of test conditions. This flowfield database is being used to better understand mixing and heat transfer phenomena in small rockets, influence the numerical modeling of small rocket flowfields, and characterize small rocket components. The diagnostic chamber designs include: a chamber design for gathering wall temperature profiles to be used as boundary conditions in a finite element heat flux model; a chamber design for gathering inner wall temperature and static pressure profiles; and optically-accessible chamber designs, to be used with a suite of laser-based diagnostics for gathering local species concentration, temperature, density, and velocity profiles. These chambers were run with gaseous hydrogen/gaseous oxygen (GH2/GO2) propellants, while subsequent versions will be run on liquid oxygen/hydrocarbon (LOX/HC) propellants. The purpose, design, and initial test results of these small rocket flowfield diagnostic chambers are summarized.

Morren, Sybil↗