Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sensor and process anomalies”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Attention Focusing and Anomaly Detection in Systems Monitoring

Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by. In addition, to make the monitoring process efficient, and to avoid the potential for information overload on human operators, attention focusing must also be addressed. When an anomaly occurs, more often than not several sensors are affected, and the partially redundant information they provide can be confusing, particularly in a crisis situation where a response is needed quickly.

systems↗
NASA NTRSDate not supplied

Short Time Scale Stability Monitoring of GOES-16 Visible Channels by Utilizing Daily Inter-Calibration Events with both VIIRS and MODIS Sensors

The CERES project relies on MODIS, VIIRS and geostationary (GEO) imager retrieved cloud properties to compute surface fluxes and convert CERES and GEO radiances into TOA fluxes. The CERES TOA and surface fluxes need to be of climate quality and any anomaly or discontinuity in the calibration of the MODIS, VIIRS, GEO radiances need to be mitigated or avoided. Due to the nature of the CERES instrument calibration, there is a lag time of 3 months before the processing of the CERES product. This allows the CERES team to investigate any unforeseen problems in the input datasets or GEO calibration discontinuities or anomalies before processing. The CERES geostationary imager calibration team is developing a daily monitoring system of GEO, MODIS and VIIRS visible channel radiances in order to detect any day to day discontinuities as part of the CERES/GEO coincident ray-matching calibration efforts. a GEO discontinuity can be detected using two MODIS and 2 VIIRS sensors simultaneously, thus increasing the sampling greatly over a single GEO/LEO radiance pairs. This method is being automated and has already detected three erroneous radiometric calibration events, which were verified with the GOES-16 event log page. One advantage of daily monitoring is that the time period needed to verify calibration drifts is reduced and the confidence to detect even smaller magnitudes of the calibration drift is increased over monthly monitoring. By utilizing Terra and Aqua MODIS and NPP and NOAA20 VIIRS imagers to inter-calibrate GOES-16, the GOES-16 calibration can be referenced to anyone of these imagers. If the CERES project transitions between the Aqua-MODIS imager to the NOAA20 VIIRS imager, the NOAA-20 VIIRS imager can be radiometrically scale to Aqua-MODIS calibration, thus avoiding a GOES-16 calibration discontinuity.

David Robert Doelling↗
NASA NTRS1980

Concepts for on-board satellite image registration, volume 1

The NASA-NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. One very specific area of interest is the preprocessing required to register imaging sensor data which have been distorted by anomalies in subsatellite-point position and/or attitude control. The concepts and considerations involved in using state-of-the-art positioning systems such as the Global Positioning System (GPS) in concert with state-of-the-art attitude stabilization and/or determination systems to provide the required registration accuracy are discussed with emphasis on assessing the accuracy to which a given image picture element can be located and identified, determining those algorithms required to augment the registration procedure and evaluating the technology impact on performing these procedures on-board the satellite.

Ruedger, W. H.↗
NASA NTRS2011

Continued Development of Meandering Winding Magnetometer (MWM (Register Trademark)) Eddy Current Sensors for the Health Monitoring, Modeling and Damage Detection of Composite Overwrapped Pressure Vessels

Composite Overwrapped Pressure Vessels (COPVs) are used in essentially all NASA spacecraft, launch. vehicles and payloads to contain high-pressure fluids for propulsion, life support systems and science experiments. Failure of any COPV either in flight or during ground processing would result in catastrophic damage to the spacecraft or payload, and could lead to loss of life. Therefore, NASA continues to investigate new methods to non-destructively inspect (NDE) COPVs for structural anomalies and to provide a means for in-situ structural health monitoring (SHM) during operational service. Partnering with JENTEK Sensors, engineers at NASA, Kennedy Space Center have successfully conducted a proof-of-concept study to develop Meandering Winding Magnetometer (MWM) eddy current sensors designed to make direct measurements of the stresses of the internal layers of a carbon fiber composite wrapped COPV. During this study three different MWM sensors were tested at three orientations to demonstrate the ability of the technology to measure stresses at various fiber orientations and depths. These results showed good correlation with actual surface strain gage measurements. MWM-Array technology for scanning COPVs can reliably be used to image and detect mechanical damage. To validate this conclusion, several COPVs were scanned to obtain a baseline, and then each COPV was impacted at varying energy levels and then rescanned. The baseline subtracted images were used to demonstrate damage detection. These scans were performed with two different MWM-Arrays. with different geometries for near-surface and deeper penetration imaging at multiple frequencies and in multiple orientations of the linear MWM drive. This presentation will include a review of micromechanical models that relate measured sensor responses to composite material constituent properties, validated by the proof of concept study, as the basis for SHM and NDE data analysis as well as potential improvements including design changes to miniaturize and make the sensors durable in the vacuum of space

Russell, Richard↗
NASA NTRS2012

Shuttle Transportation System Case-Study Development

A case-study collection was developed for NASA's Space Shuttle Program. Using lessons learned and documented by NASA KSC engineers, analysts, and contractors, decades of information related to processing and launching the Space Shuttle was gathered into a single database. The goal was to provide educators with an alternative means to teach real-world engineering processes and to enhance critical thinking, decision making, and problem solving skills. Suggested formats were created to assist both external educators and internal NASA employees to develop and contribute their own case-study reports to share with other educators and students. Via group project, class discussion, or open-ended research format, students will be introduced to the unique decision making process related to Shuttle missions and development. Teaching notes, images, and related documents will be made accessible to the public for presentation of Space Shuttle reports. Lessons investigated included the engine cutoff (ECO) sensor anomaly which occurred during mission STS-114. Students will be presented with general mission infom1ation as well as an explanation of ECO sensors. The project will conclude with the design of a website that allows for distribution of information to the public as well as case-study report submissions from other educators online.

Ransom, Khadijah↗
NASA NTRS1990

Gamma Ray Observatory (GRO) OBC attitude error analysis

This analysis involves an in-depth look into the onboard computer (OBC) attitude determination algorithm. A review of TRW error analysis and necessary ground simulations to understand the onboard attitude determination process are performed. In addition, a plan is generated for the in-flight calibration and validation of OBC computed attitudes. Pre-mission expected accuracies are summarized and sensitivity of onboard algorithms to sensor anomalies and filter tuning parameters are addressed.

Harman, R. R.↗
NASA NTRS1989

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

Gupta, U. K.↗
NASA NTRS2003

Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking

A general method of anomaly detection from time-correlated sensor data is disclosed. Multiple time-correlated signals are received. Their cross-signal behavior is compared against a fixed library of invariants. The library is constructed during a training process, which is itself data-driven using the same time-correlated signals. The method is applicable to a broad class of problems and is designed to respond to any departure from normal operation, including faults or events that lie outside the training envelope.

James, Mark L.↗
NASA NTRS2008

Intelligent Integrated Health Management for a System of Systems

An intelligent integrated health management system (IIHMS) incorporates major improvements over prior such systems. The particular IIHMS is implemented for any system defined as a hierarchical distributed network of intelligent elements (HDNIE), comprising primarily: (1) an architecture (Figure 1), (2) intelligent elements, (3) a conceptual framework and taxonomy (Figure 2), and (4) and ontology that defines standards and protocols. Some definitions of terms are prerequisite to a further brief description of this innovation: A system-of-systems (SoS) is an engineering system that comprises multiple subsystems (e.g., a system of multiple possibly interacting flow subsystems that include pumps, valves, tanks, ducts, sensors, and the like); 'Intelligent' is used here in the sense of artificial intelligence. An intelligent element may be physical or virtual, it is network enabled, and it is able to manage data, information, and knowledge (DIaK) focused on determining its condition in the context of the entire SoS; As used here, 'health' signifies the functionality and/or structural integrity of an engineering system, subsystem, or process (leading to determination of the health of components); 'Process' can signify either a physical process in the usual sense of the word or an element into which functionally related sensors are grouped; 'Element' can signify a component (e.g., an actuator, a valve), a process, a controller, an actuator, a subsystem, or a system; The term Integrated System Health Management (ISHM) is used to describe a capability that focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) not just data to control systems for safe and effective operation. A major novel aspect of the present development is the concept of intelligent integration. The purpose of intelligent integration, as defined and implemented in the present IIHMS, is to enable automated analysis of physical phenomena in imitation of human reasoning, including the use of qualitative methods. Intelligent integration is said to occur in a system in which all elements are intelligent and can acquire, maintain, and share knowledge and information. In the HDNIE of the present IIHMS, an SoS is represented as being operationally organized in a hierarchical-distributed format. The elements of the SoS are considered to be intelligent in that they determine their own conditions within an integrated scheme that involves consideration of data, information, knowledge bases, and methods that reside in all elements of the system. The conceptual framework of the HDNIE and the methodologies of implementing it enable the flow of information and knowledge among the elements so as to make possible the determination of the condition of each element. The necessary information and knowledge is made available to each affected element at the desired time, satisfying a need to prevent information overload while providing context-sensitive information at the proper level of detail. Provision of high-quality data is a central goal in designing this or any IIHMS. In pursuit of this goal, functionally related sensors are logically assigned to groups denoted processes. An aggregate of processes is considered to form a system. Alternatively or in addition to what has been said thus far, the HDNIE of this IIHMS can be regarded as consisting of a framework containing object models that encapsulate all elements of the system, their individual and relational knowledge bases, generic methods and procedures based on models of the applicable physics, and communication processes (Figure 2). The framework enables implementation of a paradigm inspired by how expert operators monitor the health of systems with the help of (1) DIaK from various sources, (2) software tools that assist in rapid visualization of the condition of the system, (3) analical software tools that assist in reasoning about the condition, (4) sharing of information via network communication hardware and software, and (5) software tools that aid in making decisions to remedy unacceptable conditions or improve performance.

Smith, Harvey↗
DOE OSTI2023

Application of Machine Learning to Monitor Metal Powder-Bed Fusion Additive Manufacturing Processes

The use of additive manufacturing (AM) is increasing for high-value, critical applications across a range of disparate industries. This article presents a discussion of high-valued engineering components predominantly used in the aerospace and medical industries. Applications involving metal AM, including methods to identify pores and voids in AM materials, are the focus. The article reviews flaw formation in laser-based powder-bed fusion, summarizes sensors used for in situ process monitoring, and outlines advances made with in situ process-monitoring data to detect AM process flaws. It reviews investigations of ML-based strategies, identifies challenges and research opportunities, and presents strategies for assessing anomaly detection performance.

Reutzel, Edward W.↗
NASA NTRSDate not supplied

Homogenization of Satellite Based Hyperspectral Infrared Sounder Data To Build Long Term Climate Record

Building long term climate record using data from multiple hyperspectral Infrared (IR)sounders requires the homogenization of different data record to ensure the consistency andcontinuity. Such a requirement comes from two perspectives: 1) the need to adjust theoverlapping measurements of different sounders to ensure the radiometric consistency in thespectral radiance domain; 2) the need for a rigorously defined scheme to ensure the radiometricconsistency being transferred to the essential climate variables derived from the radiance record.We develop a solution that uses a spectral fingerprinting scheme to derive anomalies of keyclimate variables from long term spectral radiance data record constructed using both AIRS andCrIS observations aboard AQUA, SNPP and JPSS satellites. The fingerprinting scheme usescommon radiative kernels for all sounder measurements and therefore effectively avoids thealgorithm introduced inconsistency in retrieved geophysical variables. Our approach uses aunified sampling scheme to match AIRS and CrIS observations in both spectral and spatial-temporal domain, facilitating the intercomparison of spectral radiances from different sensors(platforms). The optimized liner inversion scheme allows the direct quantification and thereforethe adjustment for the impact on the derived climate anomalies imposed by potential radiometricinconsistency between the overlapping measurements. Such a scheme also enables the low-latency data processing of long term hyperspectral sounder data records. This paper provides a detailed introduction of the spectral fingerprinting methodology.Also introduced here is the climate fingerprinting Sounder Product (ClimFiSP) developed basedon the fingerprinting methodology. ClimFiSP products include the space-time averagedproperties of key climate variables that are derived from the long-term, space-time averagedradiances from AQUA-AIRS, SNPP-CrIS, and JPSS1-CrIS. ClimFiSP will be available to usersthrough NASA'sGoddard Earth Sciences Data and Information Services Center (GES DISC).

Wan Wu↗
NASA NTRS1993

Intelligent neuroprocessors for in-situ launch vehicle propulsion systems health management

Efficacy of existing on-board propulsion systems health management systems (HMS) are severely impacted by computational limitations (e.g., low sampling rates); paradigmatic limitations (e.g., low-fidelity logic/parameter redlining only, false alarms due to noisy/corrupted sensor signatures, preprogrammed diagnostics only); and telemetry bandwidth limitations on space/ground interactions. Ultra-compact/light, adaptive neural networks with massively parallel, asynchronous, fast reconfigurable and fault-tolerant information processing properties have already demonstrated significant potential for inflight diagnostic analyses and resource allocation with reduced ground dependence. In particular, they can automatically exploit correlation effects across multiple sensor streams (plume analyzer, flow meters, vibration detectors, etc.) so as to detect anomaly signatures that cannot be determined from the exploitation of single sensor. Furthermore, neural networks have already demonstrated the potential for impacting real-time fault recovery in vehicle subsystems by adaptively regulating combustion mixture/power subsystems and optimizing resource utilization under degraded conditions. A class of high-performance neuroprocessors, developed at JPL, that have demonstrated potential for next-generation HMS for a family of space transportation vehicles envisioned for the next few decades, including HLLV, NLS, and space shuttle is presented. Of fundamental interest are intelligent neuroprocessors for real-time plume analysis, optimizing combustion mixture-ratio, and feedback to hydraulic, pneumatic control systems. This class includes concurrently asynchronous reprogrammable, nonvolatile, analog neural processors with high speed, high bandwidth electronic/optical I/O interfaced, with special emphasis on NASA's unique requirements in terms of performance, reliability, ultra-high density ultra-compactness, ultra-light weight devices, radiation hardened devices, power stringency, and long life terms.

Gulati, S.↗
DOE OSTI2025

Detecting Process Equipment Failures Using Acoustic Data and Machine Learning

Nuclear power plant (NPP) process equipment such as fans, motors, valves, and pumps generate frequent or continuous noise, and deviations from the normal operational sounds made by this equipment can indicate potential issues. These deviations can be identified via automated acoustic anomaly detection, which involves using acoustic sensors (i.e., microphones) alongside detection algorithms to continuously monitor for changes in acoustic signatures. This task is made challenging by the substantial background noise that exists, such as operators opening and closing doors, manipulating valves, and conversing—in addition to typical plant noises. In collaboration with a nuclear power utility partner, this effort assessed the efficacy of acoustic anomaly detection when using a specific acoustic sensor that compresses data into a fixed set of features that are transferable over a standard Internet of Things communication protocol, thereby improving usability but potentially degrading detection performance. Two methods of performing automated acoustic anomaly detection were evaluated: one-class support vector machine (OC-SVM) and isolation forest (iForest). To enable the use of high-quality acoustic data encompassing both normal and anomalous conditions, the study utilized the publicly available Malfunctioning Industrial Machine Investigation and Inspection dataset, which includes real measured acoustic sensor data for a range of equipment types, model numbers, and signal-to-noise ratios (SNRs), along with a benchmark set of detection results. Using this dataset, the methods were tested and then compared against the benchmark results. The results indicated that although the specific acoustic sensor did not enable as rich a feature set extraction, the proposed methods with the limited feature set performed just as well. This provides solid justification for both the methods and the use of the proposed acoustic sensor.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS1984

The pointing system for Space Telescope

This paper provides a description of the Space Telescope (ST) Pointing System (PS), and an overview of the pointing operations and procedures that support celestial observations. It is aimed at indicating to the user-astronomer the ST pointing capabilities and the mechanics of insuring the presence of the correct star in an instrument aperture. The paper begins by summarizing the general requirements regarding image stability and pointing accuracy to which the ST is being designed. This is followed by a description of the PS, in which primary elements are rate gyros, star sensors, reaction wheels, and an onboard digital computer. The Fine Guidance System is the star sensor that provides the precise, long term celestial reference and is given special emphasis, since its autonomous modes are so intimately tied to the acquisition process. A description of a nominal acquisition sequence is given, and some strategies for dealing with acquisition and pointing anomalies are discussed.

Nurre, G. S.↗
NASA NTRS2016

The "Puck" Energetic Charged Particle Detector: Design, Heritage, and Advancements

Energetic charged particle detectors characterize a portion of the plasma distribution function that plays critical roles in some physical processes, from carrying the currents in planetary ring currents to weathering the surfaces of planetary objects. For several low-resource missions in the past, the need was recognized for a low-resource but highly capable, mass-species-discriminating energetic particle sensor that could also obtain angular distributions without motors or mechanical articulation. This need led to the development of a compact Energetic Particle Detector (EPD), known as the "Puck" EPD (short for hockey puck), that is capable of determining the flux, angular distribution, and composition of incident ions between an energy range of approximately 10 kiloelectronvolts to several megaelectronvolts. This sensor makes simultaneous angular measurements of electron fluxes from the tens of kiloelectronvolts to about 1 megaelectronvolt. The same measurements can be extended down to approximately 1 kiloelectronvolt per nucleon,with some composition ambiguity. These sensors have a proven flight heritage record that includes missions such as MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) and New Horizons, with multiple sensors on each of Juno, Van Allen Probes, and Magnetospheric Multiscale. In this review paper we discuss the Puck EPD design, its heritage, unexpected results from these past missions and future advancements. We also discuss high-voltage anomalies that are thought to be associated with the use of curved foils, which is a new foil manufacturing processes utilized on recent Puck EPD designs. Finally, we discuss the important role Puck EPDs can potentially play in upcoming missions.

Clark, G.↗
NASA NTRS2009

Terminal Descent Sensor Simulation

Sulcata software simulates the operation of the Mars Science Laboratory (MSL) radar terminal descent sensor (TDS). The program models TDS radar antennas, RF hardware, and digital processing, as well as the physics of scattering from a coherent ground surface. This application is specific to this sensor and is flexible enough to handle end-to-end design validation. Sulcata is a high-fidelity simulation and is used for performance evaluation, anomaly resolution, and design validation. Within the trajectory frame, almost all internal vectors are represented in whatever coordinate system is used to represent platform position. The trajectory frame must be planet-fixed. The platform body frame is specified relative to arbitrary reference points relative to the platform (spacecraft or test vehicle). Its rotation is a function of time from the trajectory coordinate system specified via dynamics input (file for open loop, callback for closed loop). Orientation of the frame relative to the body is arbitrary, but constant over time. The TDS frame must have a constant rotation and translation from the platform body frame specified at run time. The DEM frame has an arbitrary, but time-constant, rotation and translation with respect to the simulation frame specified at run time. It has the same orientation as sigma0 frame, but is possibly translated. Surface sigma0 has the same arbitrary rotation and translation as DEM frame.

Chen, Curtis W.↗
NASA NTRSDate not supplied

RadLab and the Environmental Data Application Dashboard: Graphical and Programming Interfaces for Interrogation of Space Telemetry Data

Sensors on the International Space Station (ISS) and multiple spacecraft elsewhere in Earth orbit and in deep space continuously monitor and collect environmental data, transmitting this information back to Earth. These data include ionizing radiation and, on the ISS, CO2, relative humidity levels, and temperature, and are of great importance to space biology research. Ionizing radiation in particular has been established in ground-based experiments as being correlated with increased risk of carcinogenesis and cardiovascular and neurological effects. Looking ahead to future long duration crewed missions beyond low Earth orbit, the ability to study how factors including CO2 levels, light cycle, temperature modulate the response to ionizing radiation and microgravity is essential. To date, access to these data has been fragmented across space agencies, spacecraft, and databases. To address this issue, NASA’s Open Science Data Repository (osdr.nasa.gov) has developed two Web applications: the Environmental Data Application (EDA) and a radiation-specific RadLab. Each consists of an API (application programming interface) and an associated GUI (graphical user interface) that provide single points of access to the data. To date, OSDR has focused on the sensors from payloads and radiation detectors located on the ISS. The Web applications process telemetry information and associated data, such as spacecraft location and orientation, from multiple international databases. The applications’ request syntax enables users to interrogate these data by craft, sensor type, time range, radiation type (galactic cosmic rays, solar particle events, the contribution of the South Atlantic Anomaly), facilitating arbitrary comparisons of original source data at varying time resolutions. The applications provide programmatic access for use in computational pipelines and GUIs for data visualization and exploration, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

radiation↗
NASA NTRS2015

Sun Safe Mode Controller Design for LADEE

This paper presents the development of sun safe controllers which are designed to keep the spacecraft power positive and thermally balanced in the event an anomaly is detected. Employed by NASA's Lunar Atmosphere and Dust Environment Explorer (LADEE), the controllers utilize the measured sun vector and the spacecraft body rates for feedback control. To improve the accuracy of sun vector estimation, the least square minimization approach is applied to process the sensor data, which is proven to be effective and accurate. To validate the controllers, the LADEE spacecraft model engaging the sun safe mode was first simulated and then compared with the actual LADEE orbital fight data. The results demonstrated the applicability of the proposed sun safe controllers.

Sun Safe Control↗