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At least 991 records · Page 55

Reliability with imperfect diagnostics

A reliability estimation method for systems that continually accumulate faults because of imperfect diagnostics is developed and an application for redundant digital avionics is presented. The present method assumes that if a fault does not appear in a short period of time, it will remain hidden until a majority of components are faulty and the system fails. A certain proportion of a component's faults are detected in a short period of time, and a description of their detection is included in the reliability model. A Markov model of failure during flight for a nonreconfigurable five-plex is presented for a sequence of one-hour flights followed by maintenance.

White, A. L.↗

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.↗

Linear Spectral Analysis of Plume Emissions Using an Optical Matrix Processor

Plume spectrometry provides a means to monitor the health of a burning rocket engine, and optical matrix processors provide a means to analyze the plume spectra in real time. By observing the spectrum of the exhaust plume of a rocket engine, researchers have detected anomalous behavior of the engine and have even determined the failure of some equipment before it would normally have been noticed. The spectrum of the plume is analyzed by isolating information in the spectrum about the various materials present to estimate what materials are being burned in the engine. Scientists at the Marshall Space Flight Center (MSFC) have implemented a high resolution spectrometer to discriminate the spectral peaks of the many species present in the plume. Researchers at the Stennis Space Center Demonstration Testbed Facility (DTF) have implemented a high resolution spectrometer observing a 1200-lb. thrust engine. At this facility, known concentrations of contaminants can be introduced into the burn, allowing for the confirmation of diagnostic algorithms. While the high resolution of the measured spectra has allowed greatly increased insight into the functioning of the engine, the large data flows generated limit the ability to perform real-time processing. The use of an optical matrix processor and the linear analysis technique described below may allow for the detailed real-time analysis of the engine's health. A small optical matrix processor can perform the required mathematical analysis both quicker and with less energy than a large electronic computer dedicated to the same spectral analysis routine.

Gary, C. K.↗

Assessment of Cold Spraying Mild-Steel Powder onto Mild-Steel Substrate for Development of Waste Tank Repair System - 20515

Infrastructure for nuclear waste storage and processing (e.g., waste tanks, transfer pipelines, evaporators) at the U.S. Department of Energy (DOE) Hanford Site has been in service well beyond its original design life. Past corrosion control methods at Hanford for waste tanks have not been fully successful, as evidenced by leaks forming in tank AY-102, the first double-shell tank (DST) constructed, and significant degradation detected in the primary tanks of AP-102 and AY-101. Failure of infrastructure components can pose a significant risk to the environment, worker safety, and project schedules. Therefore, remotely deployable methods for repairing and extending the service life of the existing tank waste infrastructure are needed. Cold spray has been identified as a potential technique for performing in situ repairs and material buildup for life extension of waste storage and processing infrastructure. Cold-spray repair methods and technology are well-established and are used extensively by industry and the military for making repairs using dissimilar materials. Pacific Northwest National Laboratory is evaluating the process of making repairs using mild-steel powder applied to a mild-steel substrate to minimize the galvanic corrosion potential. This paper presents the initial results for a feasibility ('go/no-go') assessment as to whether low-density deposits with sound metallurgic bonds, to build-back steel plate material, can be achieved using existing commercial cold-spray equipment. An assessment of steel-on-steel deposit is necessary to determine if cold spray is a viable candidate for DST carbon steel plate restoration/repair and thus DST service life extension. Powder properties and preparation requirements have been investigated and operating conditions and parameters for depositing a cold-spray buildup of mild steel on a mild-steel substrate have been determined. Soundness of metallurgic bonding as a function of the operating parameters exercised and results from applying cold spray to lay a deposit over simulated small-diameter flaws in 1/2-inch mild-steel plate are presented. Application of in situ cold-spray repair to the DOE complex has the potential to reduce cost and schedule impacts associated with component failures and the need to procure and construct replacement infrastructure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Power Module Precursors and Prognostics

The ongoing work involves 1) the identification and evaluation of various electric signals as indicators to module failure and precursors to aging, and 2) the development of corresponding detection techniques. In the current phase, 1) the increase of on-state resistance is selected as the precursor to the power cycle aging of silicon carbide power MOSFET modules based on review and rest data. 2) A detection method leveraging the gate voltage fluctuations magnitude during commutation transients to inform the on-state resistance increase is investigated which has the benefit of being able to be integrated into the gate driver. A dedicated detection circuit for implementation is designed and simulated and is currently in fabrication.

ADVANCED PROPULSION SYSTEMS↗

Correlative acoustic time-of-flight spectroscopy and X-ray imaging to investigate gas-induced delamination in lithium-ion pouch cells during thermal runaway

It remains difficult to detect internal mechanical deformation and gas-induced degradation in lithium-ion batteries, especially outside specialized diagnostics laboratories. In this work, we demonstrate that electrochemical acoustic time-of-flight (EA-ToF) spectroscopy can be used as an insightful and field-deployable diagnostic/prognostic technique to sense the onset of failure. A 210 mAh commercial lithium-ion cell undergoing thermal abuse testing is probed with in situ and operando EA-ToF spectroscopy, together with simultaneous fractional thermal runaway calorimetry (FTRC) and synchrotron X-ray imaging. The combination of X-ray imaging and EA-ToF analysis provides new understanding into the through-plane mechanical deformation in lithium-ion batteries through direct visualisation and the acoustic ToF response. Internal structural changes, such as gas-induced delamination, are identified using EA-ToF spectroscopy due to variations in the attenuation and signal peak shifts. This is corroborated using X-ray imaging, demonstrating EA-ToF spectroscopy as a promising technique for detecting onset of battery failure.

25 ENERGY STORAGE↗

Deep learning model to detect various synchrophasor data anomalies

High-density synchrophasors provide valuable information for power grid situational awareness, operation and control. Unfortunately, due to factors including communication instability and hardware failure, their data quality can be greatly deteriorated by anomalies. Since the anomalies can impact the performance of the synchrophasor applications, it is of paramount significance to propose a model to detect anomalies in synchrophasor. In this study, a convolutional neural network model is established to detect and classify the anomalies in the synchrophasor measurements. Additionally, four types of anomalies observed in actual synchrophasors including erroneous patterns, random spikes, missing points and high-frequency interferences are considered in this study. The proposed model is extensively evaluated via field-collected measurements from the synchrophasor network in Jiangsu grid, China. The superior performance of the proposed model indicates the great potential of using deep learning for the detection of abnormal synchrophasor measurements.

42 ENGINEERING↗

Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis

A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.

Dempsey, Paula J.↗

Artificial Intelligence Thermostat to Detect Faults

Residential air conditioners and heat pumps often experience faults due to inadequate maintenance, which can severely reduce efficiency or even cause system failure. Common issues include dirty or clogged air filters and refrigerant leaks. These problems degrade performance and increase energy use and operating costs. This study presents a smart thermostat with embedded artificial intelligence to detect such faults and alert homeowners when maintenance is needed. The thermostat uses low-cost measurements—including return-air temperature, relative humidity, supply-air temperature, outdoor-air temperature, and condenser subcooling—to identify abnormal operations. Because different faults produce distinct response patterns, tailored algorithms are developed to recognize characteristic fault signatures. The investigation is built on a detailed co-simulation platform that couples EnergyPlus with the DOE/ORNL Heat Pump Design Model (HPDM). EnergyPlus represents the building’s dynamic environment, while HPDM is a high-fidelity, hardware-based model that can simulate fault-free performance as well as a wide range of faults, including gradual degradation such as minor refrigerant leakage. This platform provides a virtual training and testing environment that helps distinguish fault-induced behavior from normal operation and supports development of robust diagnostic algorithms. Using this framework, a Dynamic Bayesian Network was developed to identify two common faults—gradual refrigerant charge loss and indoor airflow blockage—and the AI-embedded thermostat was verified through annual building simulations.

Shen, Bo [ORNL] (ORCID:0000000336600393)↗

Feasibility of using distributed chemical sensing for CO2 leakage monitoring

The feasibility study focused on the development of new fiber for distributed chemical sensing (DCS) that will allow direct detection of CO 2 leakages in the environment. This is particularly important for monitoring well integrity for carbon capture and storage (CCS), to provide early warning for an incoming well failure and potential CO 2 leaking through it. We proposed using optical spectroscopy in optical fiber for direct detection of CO 2 . The main approach is based on Raman interrogation within gas-filled Holey Fibers (HoFs), so that the location and concentration of the gases would be provided simultaneously via backscattering. Additionally, Infrared (IR) Absorption Spectroscopy could also be used, and the architecture would be more discrete since interleaving with standard solid core fibers and Fiber Bragg Grating (FBG) sections is required to enable reflection to the I/O controls. The possible Raman length or the IR numbers of sections would be defined based on signal to noise ratio. The optical spectroscopy methodology would overcome current roadblocks to CCS, as fiber optics will allow for CO 2 (and other gases) detection in wells with direct in-situ measurements of concentration along with other important parameters such as temperature and pressure as the baseline of environment background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Adaptive model-based control systems and methods for controlling a gas turbine

Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).

Brunell, Brent Jerome↗

An expert system to perform on-line controller restructuring for abrupt model changes

Work in progress on an expert system used to reconfigure and tune airframe/engine control systems on-line in real time in response to battle damage or structural failures is presented. The closed loop system is monitored constantly for changes in structure and performance, the detection of which prompts the expert system to choose and apply a particular control restructuring algorithm based on the type and severity of the damage. Each algorithm is designed to handle specific types of failures and each is applicable only in certain situations. The expert system uses information about the system model to identify the failure and to select the technique best suited to compensate for it. A depth-first search is used to find a solution. Once a new controller is designed and implemented it must be tuned to recover the original closed-loop handling qualities and responsiveness from the degraded system. Ideally, the pilot should not be able to tell the difference between the original and redesigned systems. The key is that the system must have inherent redundancy so that degraded or missing capabilities can be restored by creative use of alternate functionalities. With enough redundancy in the control system, minor battle damage affecting individual control surfaces or actuators, compressor efficiency, etc., can be compensated for such that the closed-loop performance in not noticeably altered. The work is applied to a Black Hawk/T700 system.

Litt, Jonathan S.↗

Are Soft Short Tests Good Indicators of Internal Li-ion Cell Defects?

The self discharge test at full state of charge, may not be a good one to detect subtle defects since the li-ion chemistry has the highest self discharge at full state of charge. One should characterize self discharge versus storage time for each cell manufacturer/design to differentiate between normal self discharge and that due to a subtle manufacturing defect. The various soft short test methods indicate that if this test is carried out at full discharge (0% SOC) with all capacity removed (by lowering the current load in a stepwise manner to the same end of discharge voltage), then the cells need to be placed in storage for more than 72 hours to get a good analysis on the presence of subtle defects since it takes more than 72 hours to achieve voltage stabilization. If the cells are to be charged up even to a small percentage (ex. 1%), 72 hours are sufficient to determine issues. However, the pass/fail criteria should be based on a valid OCV decline. Less than 10 mV voltage decline is not a good method to detect subtle defects. As mentioned in the first bullet, self discharge is a competing reaction when a charge is introduced and hence a characterization of the self discharge versus storage time is required to fully correlate voltage decline to a failure due to a subtle defect. Soft short test method cannot be relied on for defect detection because cells with and without voltage decline seemed to have similar defects and characteristics. Screening methods such as internal resistance and capacity as well as a 3-sigma range for OCV, mass and dimensions should be used to screen out outliers. A very critical aspect in the understanding of subtle defects is to carry out destructive analysis of cells from every lot to confirm the quality of production and screen all cells and batteries in a stringent manner to have a high quality set of flight cells. Self Discharge Test: Fully charged cells shall be placed in Open circuit stand for 72 hours (OCV measurement twice a day); continue for total of 14 days with 1 reading per day 2. Soft Short Test 1: Fully charge; cells discharged to manufacturer's end of disch. Voltage (EODV) cutoff at C/5 rate; stand for 30 minutes; discharge with C/500 to the same EODV. stand for another 30 minutes; discharge the cells again using C/1000 current to the same EODV. OCV measurements twice a day for 72 hours and then for total of 14 days (data collection same as in 1.) 3. Soft Short Test 2: Fully charge; cells discharged to the manuf. EODV with a C/13 constant current; provide a 10 hour rest, discharge again to the same EODV with a current of C/250, provide a 10 hour rest, discharge again using a C/250 rate, provide a 24 hour rest, charge using C/250 to 3.15 V (for ~12 hours). OCV measurements twice a day for at 72 hours. (data collection same as in 1.) 4. Soft Short Test 3: Fully charge; cells shall be discharged using C/10 current to manuf. EODV. Allow the cell to remain at Open circuit for 10 seconds. Discharge the cell at C/20 rate to the same EODV, hold open circuit for 24 hours. Discharge the cells at C/200 rate to the same end of voltage cutoff and hold open circuit for 24 hours. Discharge the cells one more time at C/200 rate to the same EODV and hold open circuit for 36 hours. Charge at C/200 rate to 3.15 V and hold for 3 days. Record OCV during the open circuit stand periods every 12 hours and at the beginning and end of the 3 day hold (include the 12 hour OCV recording during this time also). Capacity Cycling: Cells with declining voltages - one cell from each manufacturer chosen for cycling Destructive Physical Analysis (DPA): Cells with and without decline chosen from each lot for DPA.

Jeevarajan, J.↗

Unsupervised Process Anomaly Detection and Identification Using the Leave-One-Variable-Out Approach

Automated anomaly detection and identification can signal equipment issues and pinpoint causes in large-scale industrial systems. For systems with limited failure history, unsupervised machine learning methods can be utilized as they do not require past failures. This study introduces the leave-one-variable-out (LOVO) model, which masks one variable at a time to predict the others, learning underlying process correlations. Detection performance was assessed with synthetic and experimental data, while identification performance used only synthetic data due to its ability to generate labeled anomaly types. For detection using synthetic data, the LOVO model generally outperformed comparative models; while using experimental data, the comparative methods outperformed the LOVO model. However, the comparative methods required selecting a latent size, and these conclusions pertain to using the optimal size. In practice, it would not be feasible to always select the optimal value, and incorrect selections impacted performance. In contrast, the LOVO model does not require a latent space. For identification using synthetic data, the LOVO model was slightly outperformed in interpretability and repeatability but still demonstrated impressive results. These outcomes suggest that the LOVO model is an effective model and may be more easily implemented without the challenging tuning process of selecting a latent size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An experimental study of the mechanism of failure of rocks under borehole jack loading

Laboratory and field tests with an experimental jack and an NX-borehole jack are reported. The following conclusions were made: Under borehole jack loading, a circular opening in a brittle solid fails by tensile fracturing when the bearing plate width is not too small. Two proposed contact stress distributions can explain the mechanism of tensile fracturing. The contact stress distribution factor is a material property which can be determined experimentally. The borehole tensile strength is larger than the rupture flexural strength. Knowing the magnitude and orientation of the in situ stress field, borehole jack test results can be used to determine the borehole tensile strength. Knowing the orientation of the in situ stress field and the flexural strength of the rock substance, the magnitude of the in situ stress components can be calculated. The detection of very small cracks is essential for the accurate determination of the failure loads which are used in the calculation of strengths and stress components.

Van, T. K.↗

Transmission Bearing Damage Detection Using Decision Fusion Analysis

A diagnostic tool was developed for detecting fatigue damage to rolling element bearings in an OH-58 main rotor transmission. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting bearing surface fatigue pitting damage. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from tests performed in the NASA Glenn 500 hp Helicopter Transmission Test Stand. Data was collected during experiments performed in this test rig when two unanticipated bearing failures occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears duplex ball bearings and spiral bevel pinion triplex ball bearings in a main rotor transmission.

Dempsey, Paula J.↗

A Near-Term Concept for Trajectory Based Operations with Air/Ground Data Link Communication

An operating concept and required system components for trajectory-based operations with air/ground data link for today's en route and transition airspace is proposed. Controllers are fully responsible for separation as they are today, and no new aircraft equipage is required. Trajectory automation computes integrated solutions to problems like metering, weather avoidance, traffic conflicts and the desire to find and fly more time/fuel efficient flight trajectories. A common ground-based system supports all levels of aircraft equipage and performance including those equipped and not equipped for data link. User interface functions for the radar controller's display make trajectory-based clearance advisories easy to visualize, modify if necessary, and implement. Laboratory simulations (without human operators) were conducted to test integrated operation of selected system components with uncertainty modeling. Results are based on 102 hours of Fort Worth Center traffic recordings involving over 37,000 individual flights. The presence of uncertainty had a marginal effect (5%) on minimum-delay conflict resolution performance, and windfavorable routes had no effect on detection and resolution metrics. Flight plan amendments and clearances were substantially reduced compared to today s operations. Top-of-descent prediction errors are the largest cause of failure indicating that better descent predictions are needed to reliably achieve fuel-efficient descent profiles in medium to heavy traffic. Improved conflict detections for climbing flights could enable substantially more continuous climbs to cruise altitude. Unlike today s Conflict Alert, tactical automation must alert when an altitude amendment is entered, but before the aircraft starts the maneuver. In every other failure case tactical automation prevented losses of separation. A real-time prototype trajectory trajectory-automation system is running now and could be made ready for operational testing at an en route Center in 1-2 years.

McNally, David↗

Deep Space Network Antenna Logic Controller

The Antenna Logic Controller (ALC) software controls and monitors the motion control equipment of the 4,000-metric-ton structure of the Deep Space Network 70-meter antenna. This program coordinates the control of 42 hydraulic pumps, while monitoring several interlocks for personnel and equipment safety. Remote operation of the ALC runs via the Antenna Monitor & Control (AMC) computer, which orchestrates the tracking functions of the entire antenna. This software provides a graphical user interface for local control, monitoring, and identification of faults as well as, at a high level, providing for the digital control of the axis brakes so that the servo of the AMC may control the motion of the antenna. Specific functions of the ALC also include routines for startup in cold weather, controlled shutdown for both normal and fault situations, and pump switching on failure. The increased monitoring, the ability to trend key performance characteristics, the improved fault detection and recovery, the centralization of all control at a single panel, and the simplification of the user interface have all reduced the required workforce to run 70-meter antennas. The ALC also increases the antenna availability by reducing the time required to start up the antenna, to diagnose faults, and by providing additional insight into the performance of key parameters that aid in preventive maintenance to avoid key element failure. The ALC User Display (AUD) is a graphical user interface with hierarchical display structure, which provides high-level status information to the operation of the ALC, as well as detailed information for virtually all aspects of the ALC via drill-down displays. The operational status of an item, be it a function or assembly, is shown in the higher-level display. By pressing the item on the display screen, a new screen opens to show more detail of the function/assembly. Navigation tools and the map button allow immediate access to all screens.

Ahlstrom, Harlow↗