Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “component degradation”

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.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Novel Thin Film Sensor Technology for Turbine Engine Hot Section Components

Degradation and damage that develops over time in hot section components can lead to catastrophic failure of the turbine section of aircraft engines. A range of thin film sensor technology has been demonstrated enabling on-component measurement of multiple parameters either individually or in sensor arrays including temperature, strain, heat flux, and flow. Conductive ceramics are beginning to be investigated as new materials for use as thin film sensors in the hot section, leveraging expertise in thin films and high temperature materials. The current challenges are to develop new sensor and insulation materials capable of withstanding the extreme hot section environment, and to develop techniques for applying sensors onto complex high temperature structures for aging studies of hot propulsion materials. The technology research and development ongoing at NASA Glenn Research Center for applications to future aircraft, launch vehicles, space vehicles, and ground systems is outlined.

Wrbanek, John D.↗
NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗
NASA NTRS2003

ASRC Aerospace Corporation Selects Dynamically Reconfigurable Anadigm(Registered Trademark) FPAA For Advanced Data Acquisition System

Anadigm(registered trademark) today announced that ASRC Aerospace Corporation has designed Anadigm's dynamically reconfigurable Field Programmable Analog Array (FPAA) technology into an advanced data acquisition system developed under contract for NASA. ASRC Aerospace designed in the Anadigm(registered trademark) FPAA to provide complex analog signal conditioning in its intelligent, self-calibrating, and self-healing advanced data acquisition system (ADAS). The ADAS has potential applications in industrial, manufacturing, and aerospace markets. This system offers highly reliable operation while reducing the need for user interaction. Anadigm(registered trademark)'s dynamically reconfigurable FPAAs can be reconfigured in-system by the designer or on the fly by a microprocessor. A single device can thus be programmed to implement multiple analog functions and/or to adapt on-the-fly to maintain precision operation despite system degradation and aging. In the case of the ASRC advanced data acquisition system, the FPAA helps ensure that the system will continue to operating at 100% functionality despite changes in the environment, component degradation, and/or component failures.

Mata, Carlos T.↗
NASA NTRS2001

Evaluating Manufacturing and Assembly Errors in Rotating Machinery to Enhance Component Performance

Manufacturing and assembly phases play a crucial role in providing products that meet the strict functional specifications associated with rotating machinery components. The errors resulting during the manufacturing and assembly of such components are correlated with the vibration and noise emanating from the final system during its operational lifetime. Vibration and noise are especially unacceptable elements in high-risk systems such as helicopters, resulting in premature component degradation and an unsafe flying environment. In such applications, individual components often are subject to 100% inspection prior to assembly, as well as during operation through rigorous maintenance, resulting in increased product development cycles and high production and operation costs. In this work, we focus on providing designers and manufacturing engineers with a technique to evaluate vibration modes and levels for each component or subsystem prior to putting them into operation. This paper presents a preliminary investigation of the correlation between vibrations and manufacturing and assembly errors using an experimental test rig, which simulates a simple bearing and shaft arrangement. A factorial design is used to study the effects of: 1) different manufacturing instances; 2) different assembly instances; and, 3) varying shaft speeds. The results indicate a correlation between manufacturing or assembly errors and vibrations measured from accelerometers. Challenges in developing a tool for DFM are identified, followed by a discussion of future work, including a real-world application to helicopter transmission vibrations.

Tumer, Irem Y.↗
NASA NTRS1993

Enhancements to the Engine Data Interpretation System (EDIS)

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The results of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Hofmann, Martin O.↗
NASA NTRS1993

Enhancements to the Engine Data Interpretation System (EDIS)

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The result of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Hofmann, Martin O.↗
NASA NTRS2002

Advanced Self-Calibrating, Self-Repairing Data Acquisition System

An improved self-calibrating and self-repairing Data Acquisition System (DAS) for use in inaccessible areas, such as onboard spacecraft, and capable of autonomously performing required system health checks, failure detection. When required, self-repair is implemented utilizing a "spare parts/tool box" system. The available number of spare components primarily depends upon each component's predicted reliability which may be determined using Mean Time Between Failures (MTBF) analysis. Failing or degrading components are electronically removed and disabled to reduce power consumption, before being electronically replaced with spare components.

Pedro J Medelius↗
NASA NTRS1989

Model-based quantification of image quality

In 1982, Park and Schowengerdt published an end-to-end analysis of a digital imaging system quantifying three principal degradation components: (1) image blur - blurring caused by the acquisition system, (2) aliasing - caused by insufficient sampling, and (3) reconstruction blur - blurring caused by the imperfect interpolative reconstruction. This analysis, which measures degradation as the square of the radiometric error, includes the sample-scene phase as an explicit random parameter and characterizes the image degradation caused by imperfect acquisition and reconstruction together with the effects of undersampling and random sample-scene phases. In a recent paper Mitchell and Netravelli displayed the visual effects of the above mentioned degradations and presented subjective analysis about their relative importance in determining image quality. The primary aim of the research is to use the analysis of Park and Schowengerdt to correlate their mathematical criteria for measuring image degradations with subjective visual criteria. Insight gained from this research can be exploited in the end-to-end design of optical systems, so that system parameters (transfer functions of the acquisition and display systems) can be designed relative to each other, to obtain the best possible results using quantitative measurements.

Hazra, Rajeeb↗
NASA NTRS2013

Wireless Sensors Pinpoint Rotorcraft Troubles

Helicopters present many advantages over fixed-wing aircraft: they can take off from and land in tight spots, they can move in any direction with relative ease, and they can hover in one area for extended periods of time. But that maneuverability comes with costs. For example, one persistent issue in helicopter maintenance and operation is that their components are subject to high amounts of wear compared to fixed-wing aircraft. In particular, the rotor drive system that makes flight possible undergoes heavy vibration during routine performance, slowly degrading components in a way that can cause failures if left unmonitored. The level of attention required to ensure flight safety makes helicopters very expensive to maintain. As a part of NASA s Fundamental Aeronautics Program, the Subsonic Rotary Wing Project seeks to advance knowledge about and improve prediction capabilities for rotorcraft, with the aim of developing technology that will meet future civilian requirements like higher efficiency and lower noise flights. One of the program s goals is to improve technology to detect and assess the health of critical components in rotorcraft drive systems.

Source record↗
NASA NTRSDate not supplied

Developing Deep Learning Models for System Remaining Useful Life Predictions: Application to Aircraft Engines

Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process and down stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.

Prognostics↗
NASA NTRS2005

Application of a Constant Gain Extended Kalman Filter for In-Flight Estimation of Aircraft Engine Performance Parameters

An approach based on the Constant Gain Extended Kalman Filter (CGEKF) technique is investigated for the in-flight estimation of non-measurable performance parameters of aircraft engines. Performance parameters, such as thrust and stall margins, provide crucial information for operating an aircraft engine in a safe and efficient manner, but they cannot be directly measured during flight. A technique to accurately estimate these parameters is, therefore, essential for further enhancement of engine operation. In this paper, a CGEKF is developed by combining an on-board engine model and a single Kalman gain matrix. In order to make the on-board engine model adaptive to the real engine s performance variations due to degradation or anomalies, the CGEKF is designed with the ability to adjust its performance through the adjustment of artificial parameters called tuning parameters. With this design approach, the CGEKF can maintain accurate estimation performance when it is applied to aircraft engines at offnominal conditions. The performance of the CGEKF is evaluated in a simulation environment using numerous component degradation and fault scenarios at multiple operating conditions.

Kobayashi, Takahisa↗
NASA NTRS1994

Hubble Space Telescope - First Servicing Mission

Space Shuttle mission STS-61 was the first of several planned servicing missions for HST, intended to periodically replace failed components and upgrade scientific instruments with improved versions to keep the telescope viable and productive throughout its planned 15-year lifetime. This First Servicing Mission was also intended to correct several design flaws that were detected shortly after the launch of HST. There were three overall mission objectives for the STS-61 repair mission: 1) To Restore the Planned Scientific Capabilities: One complexity of the First Servicing Mission was the necessity for adding optical elements in the light path to correct the spherical aberration. These corrective optics were required to provide the quantitative science capability to enable key scientific programs to be carried out as originally planned. The addition of the COSTAR and the installation of WFPC2 both contributed to recovering these capabilities. 2) To Restore the Reliability of Vehicle Systems: Failed or degraded components had depleted some of the original subsystem redundancy, which had to be restored to allow continued science operations until the next servicing mission in 1997. Anomalous components that required servicing included the solar arrays, gyroscope sensing units, gyroscope electronics, magnetometers, solar array drive electronics, and electrical fuses. 3) To Validate the On-Orbit Servicing Concept for HST: Validation of the concept of on-orbit servicing as the way to achieve HST's full 15-year life was required to provide a foundation for future servicing missions.

Source record↗
NASA NTRS1974

ATS-F spacecraft - An EMC challenge

The Applications Technology Satellite F (ATS-F) is the latest of a series of satellites for communications, scientific experiments, and data collection. The physical configuration of the spacecraft is examined along with operational characteristics and EMC management and control. Predicted and encountered problems are discussed, giving attention to wiring pick-up and reradiation, input rectification and bias off-set, intermodulation products, harmonics, component degradation, electroexplosive devices, spacecraft test complex vulnerability, and launch environment testing. Approaches used for locating the problems are considered and a description is given of the key factors and constraints in achieving EMC.

Kampinsky, A.↗
NASA NTRS1975

ATS-6 spacecraft - An EMC challenge

A series of analytical, measurement, and experimental EMI tests were performed on ATS-6. The EMC problems encountered included: (1) wiring pickup and reradiation, (2) input rectification and bias offset, (3) harmonics, (4) component degradation, (5) unbalanced shield ground, (6) inadvertent pickup, and (7) electro-explosive devices. The test program consisted of materials evaluation (with regard to shielding effectiveness, cost, weight, etc.), sun sensor RF susceptibility, cable shielding material evaluation, RF integrity of solar panels and power harnesses, anechoic chamber tests, bonding and grounding, and shielding and thermal control.

Kampinsky, A.↗
NASA NTRS1985

Paleohydrologic Implications of Valley Networks of Mars

Valley networks in the heavily cratered terrains of Mars represent an ancient epoch of hydrologic conditions greatly different from those of today. Available crater counts on the valley networks indicate formation during the high flux of impacting bodies charaterizing the early heavy bombardment phase of Martian history. Two populations of valleys are recognized in the equatorial regions of Mars: pristine and degraded. The latter probably formed at the very end of the heavy bombardment phase, extending into the post-heavy bombardment by formation in the intercrater plains. Pristine valleys generally form segments of larger networks with degraded components. This suggests that valley formation was a prolonged process coeval with the heavy bombardment period and extending just beyond that period in martian history. The pristine networks and pristine portions of compound networks on Mars show morphological attributes consistent with an origin by headward growth through spring sapping. On Earth spring sapping occurs where groundwater out-streamflow can be generated by insolation changes associated with orbital parameters or with geothermal effects, such as might be associated with impact or with the volcanic emplacement of the intercrater plains. Thus, it is appropriate to specify the most conservation deviation from modern hydrologic conditions on Mars that could account for the ancient epoch of valley formation.

Baker, V. R.↗
NASA NTRS1984

On-orbit maintenance and repair - New era in space research and industrialization

During the seventies, NASA was developing a multifunction, economical spacecraft complete with ground and spaceborne support equipment, software, and necessary documentation to facilitate a large variety of space missions on a routine and cost effective basis. In order to reduce costs and time requirements, research was conducted to identify new approaches to a reusable, low-cost spacecraft design. The result of these studies was the development of the Multimission Modular Spacecraft (MMS). Three MMS spacecraft are currently operating in orbit. These spacecraft include the two Landsat-D earth resources satellites, Landsat-4 and -5, and the Solar Maximum Mission (SMM) spacecraft. Attention is given to details regarding the MMS, the STS-41C SMM repair mission, and failure modes and component degradation.

Cepollina, F.↗
NASA NTRS1990

Fabry-Perot interferometer development for rocket engine plume spectroscopy

This paper describes a new rugged high-resolution Fabry-Perot interferometer (FPI) designed for rocket engine plume spectroscopy, which is capable of detecting spectral signatures of eroding engine components during rocket engine tests and/or flight operations. The FPI system will make it possible to predict and to respond to the incipient rocket engine failures and to indicate the presence of rocket components degradation. The design diagram of the FPI spectrometer is presented.

Bickford, R. L.↗
NASA NTRS1991

Engine throat/nozzle optics for plume spectroscopy

The Task 2.0 Engine Throat/Nozzle Optics for Plume Spectroscopy, effort was performed under the NASA LeRC Development of Life Prediction Capabilities for Liquid Propellant Rocket Engines program. This Task produced the engineering design of an optical probe to enable spectroscopic measurements within the SSME main chamber. The probe mounts on the SSME nozzle aft manifold and collects light emitted from the throat plane and chamber. Light collected by the probe is transferred to a spectrometer through a fiber optic cable. The design analyses indicate that the probe will function throughout the engine operating cycle and is suitable for both test stand and flight operations. By detecting metallic emissions that are indicative of component degradation or incipient failure, engine shutdown can be initiated before catastrophic failure. This capability will protect valuable test stand hardware and provide enhanced mission safety.

Bickford, R. L.↗