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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

An evidential reasoning extension to quantitative model-based failure diagnosis

The detection and diagnosis of failures in physical systems characterized by continuous-time operation are studied. A quantitative diagnostic methodology has been developed that utilizes the mathematical model of the physical system. On the basis of the latter, diagnostic models are derived each of which comprises a set of orthogonal parity equations. To improve the robustness of the algorithm, several models may be used in parallel, providing potentially incomplete and/or conflicting inferences. Dempster's rule of combination is used to integrate evidence from the different models. The basic probability measures are assigned utilizing quantitative information extracted from the mathematical model and from online computation performed therewith.

Gertler, Janos J.↗
NASA NTRS2009

Solder Joint Health Monitoring Testbed System

The density and pin count for Field Programmable Gate Arrays (FPGAs) has been increasing, and has exceeded current methods of solder joint inspection, making early detection of failures more problematic. These failures are a concern for both flight safety and maintenance in commercial aviation. Ridgetop Group, Inc. has developed a method for detecting solder joint failures in real time. The NASA Dryden Flight Research Center is developing a set of boards to test this method in ground environmental and accelerated testing as well as flight test on a Dryden F-15 or F-18 research aircraft. In addition to detecting intermittent and total solder joint failures, environmental data on the boards, such as temperature and vibration, will be collected and time-correlated to aircraft state data. This paper details the technical approach involved in the detection process, and describes the design process and products to date for Dryden s FPGA failure detection boards.

Delaney, Michael M.↗
NASA NTRS1993

Evaluation of a vibration diagnostic system for the detection of spur gear pitting failures

A vibration diagnostic system was used to detect spur gear surface pitting fatigue in a closed-loop spur gear fatigue test rig. The diagnostic system, comprising a personal computer with an analog-to-digital conversion board, a diagnostic system unit, and software, uses time-synchronous averaging of the vibration signal to produce a vibration image of each tooth on any gear in a transmission. Several parameters were analyzed including gear pair stress wave and raw baseband vibration, kurtosis, peak ratios, and others. The system provides limits for the various parameters and gives a warning when the limits are exceeded. Several spur gear tests were conducted with this system and vibration data analyzed at 5-min. intervals. The results presented herein show that the system is fairly effective at detecting spur gear tooth surface fatigue pitting failures.

Townsend, Dennis P.↗
NASA NTRS1993

Evaluation of a vibration diagnostic system for the detection of spur gear pitting failures

A vibration diagnostic system was used to detect spur gear surface pitting fatigue in a closed-loop spur gear fatigue test rig. The diagnostic system, comprising a personal computer with an analog-to-digital conversion board, a diagnostic system unit, and software, uses time-synchronous averaging of the vibration signal to produce a vibration image of each tooth on any gear in a transmission. Several parameters were analyzed including gear pair stress wave and raw baseband vibration, kurtosis, peak ratios, and others. The system provides limits for the various parameters and gives a warning when the limits are exceeded. Several spur gear tests were conducted with this system and vibration data analyzed at 5-min. intervals. The results presented herein show that the system is fairly effective at detecting spur gear tooth surface fatigue pitting failures.

Townsend, Dennis P.↗
DOE OSTI2021

A Method for Estimating Time-Series PV Production Loss From Solar Tracking Failures

Solar tracking system failures can dramatically reduce photovoltaic (PV) system energy output through suboptimal irradiance capture and self-shading loss. Detecting tracker failures is not always straightforward; unlike other common PV system failures like inverter outages and blown fuses which take portions of a system completely offline, tracker failures only partially reduce output power and can go unnoticed as a result. Additionally, tracker failures can take one of several forms, each with their own loss characteristics. Here we present two methods of detecting tracker failure events from time-series production data and a method for estimating the associated production loss. Compared with existing detection methods, the proposed power-based detection method showed 0-17% reductions in Type I error rate depending on weather conditions. Here, the loss model estimated production loss with low error (mean bias error = -2.3 %, root-mean-squared error = 6%) in a rudimentary validation.

14 SOLAR ENERGY↗
NASA NTRS1990

Developing a self-diagnostic system for piezoelectric sensors

Measurement techniques for developing a self-diagnostic system for piezoelectric sensors are presented. The self-diagnostic system uses two types of measurement techniques based on passive and active evaluation of the piezoelectric element. Both hard and soft failures can be detected by this system. Hard failures such as loss of sensor signal and change in sensor output resistance are determined by monitoring the sensor's output resistance, voltage or current. These are passive measurements of the sensor's output condition. Soft failures include changes in sensor calibration and mounting conditions. Soft failures are detected by measuring structural/electrical impedance of the piezoelectric sensor. Active measurement techniques are used to calculate changes in piezoelectric element properties related to soft failures. This paper describes the general operating principles of a self-diagnostic system and discusses the design of an active/passive measurement technique required for this system to function. Experimental results using two types of piezoelectric accelerometers are presented.

Flanagan, Patrick M.↗
NASA NTRS1990

Frame synchronization for a channel with different data rates

In some communication links, different data rates are used at different times on the same channel and each is assigned a separate frame synchronization (sync) marker. The frame search is completed within a finite number of frame intervals once both phase-lock and bit-sync are achieved because the incoming data rate can change. The probability of failure to frame-lock, and an upper bound of probability of false frame-lock in a frame search mode are derived for a communication link with a 10 to the -5th bit error probability. The probability of failure to detect data-rate change and the probability of false detection of data-rate change in a frame-lock mode are discussed. In a frame-lock mode, the probability of failure to detect data-rate change and probability detection of data-rate change an equal to 4.96 x 10 to the -12th. A frame-lock device can be used for the Space Station Freedom Ku-band return link.

Kwon, Hyuck M.↗
NASA NTRSDate not supplied

Experimental Observations of Damage States in Unnotched and Notched 3D Orthogonal Woven Coupons Loaded in Tension

This paper describes a series of unnotched and notched tensile tests on two 3D orthogonal woven architectures. Dog bone specimens were used for the unnotched tests, and open-hole specimens were used for the notched tests. For each architecture and test type, two specimens were loaded under monotonic displacement control to failure and two specimens were incrementally loaded to failure in five steps. X-ray computed tomography (CT) was used to characterize the woven architecture and defects on each specimen prior to testing. Digital image correlation (DIC) images were obtained from both sides of the specimen throughout the loading and unloading. Acoustic emission (AE) data were also continuously acquired throughout the loading. For the incremental tests, X-ray CT was used to document the damage progression after each load increment. The damage progression was analyzed based on the results from these three techniques. The results for both architectures and test specimens followed a pattern where matrix cracks formed at the surface perpendicular to the tensile load direction. New surface cracks formed continuously throughout the loading and cracks extended in depth and width. In general, fiber failure was not detected until specimen failure.

Wade C Jackson↗
DOE OSTI2023

Virtual supervisory control and data acquisition (SCADA) automation controller

One or more virtual supervisory control and data acquisition (SCADA) controllers are provided. The virtual SCADA controller(s) may be deployed upon a detection of a failure of a physical SCADA controller. An on-site module may detect failure including a security breach which causes the physical SCADA controller to be disconnected from a network and the virtual SCADA controller(s) to take over control. The virtual SCADA controller(s) may be on-site or off-site.

Smith, Jared M.↗
DOE OSTI2022

Failure diagnosis and trend‐based performance losses routines for the detection and classification of incidents in large‐scale photovoltaic systems

Abstract Fault detection and classification in photovoltaic (PV) systems through real‐time monitoring is a fundamental task that ensures quality of operation and significantly improves the performance and reliability of operating systems. Different statistical and comparative approaches have already been proposed in the literature for fault detection; however, accurate classification of fault and loss incidents based on PV performance time series remains a key challenge. Failure diagnosis and trend‐based performance loss routines were developed in this work for detecting PV underperformance and accurately identifying the different fault types and loss mechanisms. The proposed routines focus mainly on the differentiation of failures (e.g., inverter faults) from irreversible (e.g., degradation) and reversible (e.g., snow and soiling) performance loss factors based on statistical analysis. The proposed routines were benchmarked using historical inverter data obtained from a 1.8 MWp PV power plant. The results demonstrated the effectiveness of the routines for detecting failures and loss mechanisms and the capability of the pipeline for distinguishing underperformance issues using anomaly detection and change‐point (CP) models. Finally, a CP model was used to extract significant changes in time series data, to detect soiling and cleaning events and to estimate both the performance loss and degradation rates of fielded PV systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Artificial linear brush abrasion of coatings for photovoltaic module first-surfaces

Natural soiling and the subsequent necessary cleaning of photovoltaic (PV) modules result in abrasion damage to the cover glass. The durability of the front glass has important economic consequences, including determining the use of anti-reflective and/or anti-soiling coatings as well as the method and frequency of operational maintenance (cleaning). Artificial linear brush abrasion using Nylon 6/12 bristles was therefore examined to explore the durability of representative PV first-surfaces, i.e., the surface of a module incident to direct solar radiation. Specimens examined include silane surface functionalized-, roughened (etched)-, porous silica-coated-, fluoropolymer-coated-, and ceramic (TiO 2 or ZrO 2 /SiO 2 /ZrO 2 /SiO 2 )-coated-glass, which are compared to monolithic-poly(methyl methacrylate) and -glass coupons. Characterization methods used in this study include: optical microscopy, ultraviolet–visible–near-infrared (UV-VIS-NIR) spectroscopy, sessile drop goniometry, white-light interferometry, atomic force microscopy (AFM), and depth-profiling X-ray photoelectron spectroscopy (XPS). The corresponding characteristics examined include: surface morphology, transmittance (i.e., optical performance), surface energy (water contact angle), surface roughness, scratch width and depth, and chemical composition, respectively. The study here was performed to determine coating failure modes; identify characterization methods that can detect nascent failures; compare the durability of popular contemporary coating materials; identify their corresponding damage characteristics; and compare slurry and dry-dust abrasion. This study will also aid in developing an abrasion standard for the PV industry.

14 SOLAR ENERGY↗
NASA NTRS1992

The coolest DA white dwarfs detected at soft X-ray wavelengths

New soft X-ray/EUV photometric observations of the DA white dwarfs KPD 0631 + 1043 = WD 0631 + 107 and PG 1113 + 413 = WD 1113 + 413 are analyzed. Previously reported soft X-ray detections of three other DAs and the failure to detect a fourth DA in deep Exosat observations are investigated. New ground-based spectra are presented for all of the objects, with IUE Ly-alpha spectra for some. These data are used to constrain the effective temperatures and surface gravities. The improved estimates of these parameters are employed to refer a photospheric He abundance for the hotter objects and to elucidate an effective observational low-temperature threshold for the detection of pure hydrogen DA white dwarfs at soft X-ray wavelengths.

Kidder, K. M.↗
DOE OSTI2021

Artificial Linear Brush Abrasion of Coatings for Photovoltaic Module First Surfaces

Natural soiling and the subsequent requisite cleaning of photovoltaic (PV) modules result in abrasion damage to the cover glass. The durability of the front glass has important economic consequences, including determining the use of anti-reflective and/or anti-soiling coatings as well as the method and frequency of operational maintenance (cleaning). Artificial linear brush abrasion using Nylon 6/12 bristles was therefore examined to explore the durability of representative PV first-surfaces, i.e., the surface of a module incident to direct solar radiation. Specimens examined include silane surface functionalized-, roughened (etched)-, porous silica-coated-, fluoropolymer-coated-, and ceramic (TiO2 or ZrO2/SiO2/ZrO2/SiO2)-coated-glass, which are compared to monolithic-poly(methyl methacrylate) and -glass coupons. Characterization methods used in this study include: optical microscopy, ultraviolet-visible-near-infrared (UV-VIS-NIR) spectroscopy, sessile drop goniometry, white-light interferometry, atomic force microscopy (AFM), and depth-profiling X-ray photoelectron spectroscopy (XPS). The corresponding characteristics examined include: surface morphology, transmittance (i.e., optical performance), surface energy (water contact angle), surface roughness, scratch width and depth, and chemical composition, respectively. The study here was performed to determine coating failure modes; identify characterization methods that can detect nascent failures; compare the durability of popular contemporary coating materials; identify their corresponding damage characteristics; and compare slurry and dry-dust abrasion. This study will also aid in developing an abrasion standard for the PV industry.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS1985

A preliminary evaluation of the generalized likelihood ratio for detecting and identifying control element failures in a transport aircraft

The application of the Generalized Likelihood Ratio technique to the detection and identification of aircraft control element failures has been evaluated in a linear digital simulation of the longitudinal dynamics of a B-737 aircraft. Simulation results show that the technique has potential but that the effects of wind turbulence and Kalman filter model errors are problems which must be overcome.

Bundick, W. T.↗
DOE OSTI2021

Preventing Failures By Dataset Shift Detection in Safety-Critical Graph Applications

Dataset shift refers to the problem where the input data distribution may change over time (e.g., between training and test stages). Since this can be a critical bottleneck in several safety-critical applications such as healthcare, drug-discovery, etc., dataset shift detection has become an important research issue in machine learning. Though several existing efforts have focused on image/video data, applications with graph-structured data have not received sufficient attention. Therefore, in this paper, we investigate the problem of detecting shifts in graph structured data through the lens of statistical hypothesis testing. Specifically, we propose a practical two-sample test based approach for shift detection in large-scale graph structured data. Our approach is very flexible in that it is suitable for both undirected and directed graphs, and eliminates the need for equal sample sizes. Using empirical studies, we demonstrate the effectiveness of the proposed test in detecting dataset shifts. We also corroborate these findings using real-world datasets, characterized by directed graphs and a large number of nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Resonant acoustic monitoring of damage in plug‐screw feeders

Abstract Plug‐screw feeders are critical in many industrial processes for compressing slurry materials via a rotating plug‐screw feeder. Over time, increasing plug‐screw feeder wear will eventually lead to catastrophic mechanical failure. Early detection of the wear state can prevent unplanned catastrophic failures resulting in operational shut‐downs, costly repairs, and most importantly the health and safety of workers. We present a theoretical basis for a noninvasive, in operando acoustic resonant technique to monitor the wear state of plug‐screw feeders. The technique is based on tracking the resonant acoustic modes of the plug‐screw feeder, which are sensitive to the plug‐screw feeder geometry, material, and operating conditions. We implemented a multivariate polynomial model to estimate the plug‐screw feeder wear state using multiple acoustic resonances by simulating the acoustic resonant modes for two categories of wear (tip and thread damage) that are common in plug‐screw feeders. Fitting multiple resonances to the polynomial model, we demonstrate accurate estimation of the total mass loss, as well as characterization of the type of damage (i.e., tip vs. thread). Current approaches for monitoring plug‐screw feeder wear rely on shutting down the operation and visually inspecting the plug‐screw feeder. The presented acoustic technique offers a noninvasive, in operando measurement approach that mitigates unplanned catastrophic failures. The acoustic resonance technique presented in the paper has a broad range of industrial applications including the Pharmaceutical, Mining, Integrated Biorefineries (IBR), and Additive Manufacturing industries, to name a few.

36 MATERIALS SCIENCE↗