Physics-Informed ROM Development for ISS EMU LLB-2 Condition-Based Monitoring
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Parameter inference↗
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Results for “condition monitoring”
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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Using neural networks to assist in OPAD data analysis
The space shuttle main engine (SSME) became the subject of plume emission spectroscopy in 1986 when researchers from NASA-Marshall Space Flight Center (MSFC), Arnold Engineering Development Center (AEDC), and Rocketdyne went to the SSME test stands at the NASA-Stennis Space Center and at Rocketdyne's Santa Susan Field Laboratory to optically observe the plume. Since then, plume spectral acquisitions have recorded many nominal tests and the qualitative spectral features of the SSME plume are now well established. Significant discoveries made with both wide-band and narrow-band plume emission spectroscopy systems led MSFC to promote the Optical Plume Anomaly Detection (OPAD) program with a goal of instrumenting all SSME test stands with customized spectrometer systems. A prototype OPAD system is now installed on the SSME Technology Test Bed (TTB) at MSFC. The OPAD system instrumentation consists of a broad-band, optical multiple-channel analyzer (OMA) and a narrow-band device called a polychrometer. The OMA is a high-resolution (1.5-2.0 Angstroms) 'super-spectrometer' covering the near-ultraviolet to near-infrared waveband (2800-7400 Angstroms), providing two scans per second. The polychrometer consists of sixteen narrow-band radiometers: fourteen monitoring discrete wavelengths of health and condition monitoring elements and two dedicated to monitoring background emissions. All sixteen channels are capable of providing 500 samples per second. To date, the prototype OPAD system has been used during 43 SSME firings on the TTB, collecting well over 250 megabytes of plume spectral data. One goal of OPAD data analysis is to determine interatively with the help of a computer code, SPECTRA4, developed at AEDC. Experience has shown that iteration with SPECTRA4 is an incredibly labor intensive task and not one to be performed by band. What is really needed is the 'inverse' of SPECTRA4 but the mathematical model for this inverse mapping is tenuous at best. However, the robustness of PSECTRA4 run in the 'forward' direction means that accurate input/output mappings can be obtained. If the mappings were inverted (i.e., input becomes output and output becomes input) then an 'inverse' of SPECTRA4 would be at hand but the 'model' would be specific to the data utilized and would in no way be general. Building a generalized model based upon known input/output mappings while ignoring the details of the governing physical model is possible through the use of a neural network. The research investigation described involves the development of a neural network to provide a generalized 'inverse' of SPECTRA4. The objectives of the research were to design an appropriate neural network architecture, train the network, and then evaluate its performance.
Whitaker, Kevin W.↗
Wind Turbine Contingency Control Through Generator De-Rating
Maximizing turbine up-time and reducing maintenance costs are key technology drivers for wind turbine operators. Components within wind turbines are subject to considerable stresses due to unpredictable environmental conditions resulting from rapidly changing local dynamics. In that context, systems health management has the aim to assess the state-of-health of components within a wind turbine, to estimate remaining life, and to aid in autonomous decision-making to minimize damage to the turbine. Advanced contingency control is one way to enable autonomous decision-making by providing the mechanism to enable safe and efficient turbine operation. The work reported herein explores the integration of condition monitoring of wind turbines with contingency control to balance the trade-offs between maintaining system health and energy capture. The contingency control involves de-rating the generator operating point to achieve reduced loads on the wind turbine. Results are demonstrated using a high fidelity simulator of a utility-scale wind turbine.
condition monitoring↗
Diagnostic device for monitoring the technical condition of mechanical assemblies
An automatic diagnostic device for monitoring the condition of tractor transmission gears is described. The structural noise spectrum of the gearshift box and rear axle of the tractor were analyzed in a digital computer, by an algorithm based on the multiple correlation method. The optimum assembly of operating frequencies, by use of which the errors in measurement were minimized, was selected from the entire frequency spectrum. Selected frequencies are necessary for choosing the measurement range of the diagnostic device. It turned out that, to obtain a relative error of no more than 2%, it was sufficient to use two filters, vibrating only at the frequencies carrying the maximum data of the mechanical parameter being investigated. The measurement system consists of frequency-selection filters, amplifiers and quadratic detectors, at the outlets of which constant voltages are created, which are proportional to the signal level at the frequencies selected.
Osovskiy, V. I.↗
Application of Smart Solid State Sensor Technology in Aerospace Applications
Aerospace applications require a range of chemical sensing technologies to monitor conditions in both space vehicles and aircraft operations. One example is the monitoring of oxygen. For example, monitoring of ambient oxygen (O2) levels is critical to ensuring the health, safety, and performance of humans living and working in space. Oxygen sensors can also be incorporated in detection systems to determine if hazardous leaks are occurring in space propulsion systems and storage facilities. In aeronautic applications, O2 detection has been investigated for fuel tank monitoring. However, as noted elsewhere, O2 is not the only species of interest in aerospace applications with a wide range of species of interest being relevant to understand an environmental or vehicle condition. These include combustion products such as CO, HF, HCN, and HCl, which are related to both the presence of a fire and monitoring of post-fire clean-up operations. This paper discusses the development of an electrochemical cell platform based on a polymer electrolyte, NAFION, and a three-electrode configuration. The approach has been to mature this basic platform for a range of applications and to test this system, combined with "Lick and Stick" electronics, for its viability to monitor an environment related to astronaut crew health and safety applications with an understanding that a broad range of applications can be addressed with a core technology.
Hunter, Gary W.↗
Condition sensor system and method
The condition sensor system comprises a condition detector which produces a pulse when a parameter of the monitored condition exceeds a desired threshold. A resettable condition counter counts each pulse. A resettable timer is preset to produce a particular time frame. The counter produces a condition signal when the accumulated number of pulses within the time frame is equal to or greater than a preset count. Control means responsive to the incoming pulses and to the condition signal produce control signals that control utilization devices. After a suitable delay, the last detected pulse simultaneously resets the pulse counter and the timer, and prepares them for sensing another condition occurrence within the time frame. The invention has particular utility in the process of detecting rocking motions of blind people. A controlled, audible, bio-feedback signal is provided which constitutes a warning to the blind person that he is rocking.
Polhemus, J. T.↗
Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health
Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.
Source record↗
Correlation of Electrical Resistance to CMC Stress-Strain and Fracture Behavior Under High Heat-Flux Thermal and Stress Gradients
Because SiCSiC ceramic matrix composites (CMCs) are under consideration for use as turbine engine hot-section components in extreme environments, it becomes necessary to investigate their performance and damage morphologies under complex loading and environmental conditions. Monitoring of electrical resistance (ER) has been shown as an effective tool for detecting damage accumulation of woven melt-infiltrated SiCSiC CMCs. However, ER change under complicated thermo-mechanical loading is not well understood. In this study a systematic approach is taken to determine the capabilities of ER as a relevant non-destructive evaluation technique for high heat-flux testing, including thermal gradients and localized stress concentrations. Room temperature and high temperature, laser-based tensile tests were conducted in which stress-dependent damage locations were determined using modal acoustic emission (AE) monitoring and compared to full-field strain mapping using digital image correlation (DIC). This information is then compared with the results of in-situ ER monitoring, post-test ER inspection and fractography in order to correlate ER response to convoluted loading conditions and damage evolution.
electrical resistance↗
Stennis Space Center's approach to liquid rocket engine health monitoring using exhaust plume diagnostics
Details are presented of the approach used in a comprehensive program to utilize exhaust plume diagnostics for rocket engine health-and-condition monitoring and assessing SSME component wear and degradation. This approach incorporates both spectral and video monitoring of the exhaust plume. Video monitoring provides qualitative data for certain types of component wear while spectral monitoring allows both quantitative and qualitative information. Consideration is given to spectral identification of SSME materials and baseline plume emissions.
Gardner, D. G.↗
Crop-CASMA - A Web GIS Tool for Cropland Soil Moisture Monitoring and Assessment Based on SMAP Data
Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA- a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.
Zhengwei Yang↗
Crop-CASMA - A Web GIS Tool for Cropland soil moisture Monitoring and Assessment Based on SMAP Data
Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA - a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.
Reichle, Rolf H.↗
Monitoring of Environmental Conditions in Taiga Forests Using ERS-1 SAR Data: Results From the Commissioning Phase
This paper describes the results of monitoring environmental conditions in Alaskan Taiga forests using ERS-1 SAR dara.
European Space Agency Remote Sensing Satellite (ER↗
Comparison of multispectral remote-sensing techniques for monitoring subsurface drain conditions
The following multispectral remote-sensing techniques were compared to determine the most suitable method for routinely monitoring agricultural subsurface drain conditions: airborne scanning, covering the visible through thermal-infrared (IR) portions of the spectrum; color-IR photography; and natural-color photography. Color-IR photography was determined to be the best approach, from the standpoint of both cost and information content. Aerial monitoring of drain conditions for early warning of tile malfunction appears practical. With careful selection of season and rain-induced soil-moisture conditions, extensive regional surveys are possible. Certain locations, such as the Imperial Valley, Calif., are precluded from regional monitoring because of year-round crop rotations and soil stratification conditions. Here, farms with similar crops could time local coverage for bare-field and saturated-soil conditions.
Goettelman, R. C.↗
Improved maintainability of space-based reusable rocket engines
Advanced, noninferential, noncontacting, in situ measurement technologies, combined with automated testing and expert systems, can provide continuous, automated health monitoring of critical space-based rocket engine components, requiring minimal disassembly and no manual data analysis, thus enhancing their maintainability. This paper concentrates on recent progress of noncontacting combustion chamber wall thickness condition-monitoring technologies.
Barkhoudarian, S.↗
Reducing the cognitive workload: Trouble managing power systems
The complexity of space-based systems makes monitoring them and diagnosing their faults taxing for human beings. Mission control operators are well-trained experts but they can not afford to have their attention diverted by extraneous information. During normal operating conditions monitoring the status of the components of a complex system alone is a big task. When a problem arises, immediate attention and quick resolution is mandatory. To aid humans in these endeavors we have developed an automated advisory system. Our advisory expert system, Trouble, incorporates the knowledge of the power system designers for Space Station Freedom. Trouble is designed to be a ground-based advisor for the mission controllers in the Control Center Complex at Johnson Space Center (JSC). It has been developed at NASA Lewis Research Center (LeRC) and tested in conjunction with prototype flight hardware contained in the Power Management and Distribution testbed and the Engineering Support Center, ESC, at LeRC. Our work will culminate with the adoption of these techniques by the mission controllers at JSC. This paper elucidates how we have captured power system failure knowledge, how we have built and tested our expert system, and what we believe are its potential uses.
Manner, David B.↗
(abstract) Examining Sea Ice SAR Signatures in the Arctic
This research examines the seasonal changes of the sea ice cover in the Arctic Basin as it responds to atmospheric and oceanic conditions. Monitoring this process provides a means of determining the onset and extent of the annual seasonal stages, which is thought to be an indicator for detecting climate change in the polar regions. Much of the response of sea ice to seasonal conditions results in changes in the phase of water (both in the ice and snow cover), surface roughness, and internal properties such as air bubbles. Imagery from SAR has proven to be an important tool for revealing these changes since radar backscatter is affected by both surface roughness and dielectric properties of water and salt. The major ice types and ice features may have unique SAR backscatter signatures because of the inherent variations in surface roughness, salinity, and internal properties in each category.
change surface roughness dielectric properties↗
4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications
This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011) has the potential to provide valuable information about the near-surface soil moisture state for improving land surface modeling output.
land surface modeling↗
Integrated controls and health monitoring fiberoptic shaft monitor
Recent work was performed on development optical technology to provide real time monitoring of shaft speed, shaft axial displacement, and shaft orbit of the OTVE hydrostatic bearing tester. Results show shaft axial displacement can be optically measured (at the same time as shaft orbital motion and speed) to within 0.3 mills by two fiber optic deflectometers. The final results of this condition monitoring development effort are presented.
Coleman, P.↗