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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Automated gauge reading and related systems, methods, and devices

Computing devices and methods for reading gauges are disclosed. A gauge reading method includes capturing image data corresponding to a captured image of one or more gauges, detecting one or more gauges in the captured image, cropping a detected gauge in the captured image to provide a use image including the detected gauge, and classifying the detected gauge to correlate the detected gauge with a template image. The gauge reading method also includes attempting to perform feature detection rectification on the use image to produce a rectified image of the detected gauge, performing template matching rectification on the use image to produce the rectified image responsive to a failure to perform the feature detection rectification, and estimating a gauge reading responsive to the rectified image. A computing device may implement at least a portion of a gauge reading method.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1995

Eddy-Current Detection Of Cracks In Reinforced Carbon/Carbon

Investigations of failures of components made of reinforced carbon/carbon show eddy-current flaw-detection techniques applicable to these components. Investigation focused on space shuttle parts, but applicable to other parts made of carbon/carbon materials. Techniques reveal cracks, too small to be detected visually, in carbon/carbon matrix substrates and in silicon carbide coates on substrates. Also reveals delaminations in carbon/carbon matrices. Used to characterize extents and locations of discontinuities in substrates in situations in which ultrasonic techniques and destructive techniques not practical.

Christensen, Scott V.↗
NASA NTRS1995

Autonomous control system reconfiguration for spacecraft with non-redundant actuators

The Small Satellite Technology Initiative (SSTI) 'CLARK' spacecraft is required to be single-failure tolerant, i.e., no failure of any single component or subsystem shall result in complete mission loss. Fault tolerance is usually achieved by implementing redundant subsystems. Fault tolerant systems are therefore heavier and cost more to build and launch than non-redundent, non fault-tolerant spacecraft. The SSTI CLARK satellite Attitude Determination and Control System (ADACS) achieves single-fault tolerance without redundancy. The attitude determination system system uses a Kalman Filter which is inherently robust to loss of any single attitude sensor. The attitude control system uses three orthogonal reaction wheels for attitude control and three magnetic dipoles for momentum control. The nominal six-actuator control system functions by projecting the attitude correction torque onto the reaction wheels while a slower momentum management outer loop removes the excess momentum in the direction normal to the local B field. The actuators are not redundant so the nominal control law cannot be implemented in the event of a loss of a single actuator (dipole or reaction wheel). The spacecraft dynamical state (attitude, angular rate, and momentum) is controllable from any five-element subset of the six actuators. With loss of an actuator the instantaneous control authority may not span R(3) but the controllability gramian integral(limits between t,0) Phi(t, tau)B(tau )B(prime)(tau) Phi(prime)(t, tau)d tau retains full rank. Upon detection of an actuator failure the control torque is decomposed onto the remaining active axes. The attitude control torque is effected and the over-orbit momentum is controlled. The resulting control system performance approaches that of the nominal system.

Grossman, Walter↗
NASA NTRS2006

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Motivation, benefits, and challenges for new photovoltaic material & module developments

Abstract In the last decade and longer, photovoltaic module manufacturers have experienced a rapidly growing market along with a dramatic decrease in module prices. Such cost pressures have resulted in a drive to develop and implement new module designs, which either increase performance and/or lifetime of the modules or decrease the cost to produce them. In this paper, the main motivations and benefits but also challenges for material innovations will be discussed. Many of these innovations include the use of new and novel materials in place of more conventional materials or designs. As a result, modules are being produced and sold without a long-term understanding about the performance and reliability of these new materials. This has led to unexpected new failure mechanisms occurring few years after deployment, such as potential induced degradation or backsheet cracking. None of these failure modes have been detected after the back then common single stress tests. New accelerated test approaches are based on a combination or sequence of multiple stressors that better reflect outdoor conditions. That allows for identification of new degradation modes linked to new module materials or module designs.

Oreski, G. (ORCID:0000000342239047)↗
DOE OSTI2023

Software Contribution to the L-CAPE project

The L-CAPE project utilizes asynchronous data from thousands of Linear Accelerator devices and applies data science techniques to detect anomaly of accelerator failure before the incident, as well as automatic labels of accelerator outages. The author describes her contribution progress for the L-CAPE project this summer, as well as suggestions for future interns working on the project.

Tang, Jasmine↗
NASA NTRS1973

Estimation and detection of signals in multiplicative noise

A class of detection-estimation problems on matrix Lie groups is defined in which the observation noise is multiplicative in nature. By examining the differential versions of the hypotheses, which are bilinear in nature, it is possible to derive the relevant likelihood ratio formula and the associated optimal estimation equations for the signal given the observations and the assumption that the signal is present. These estimation equations are of interest in their own right, in that they represent a finite dimensional optimal solution to a nonlinear estimation problem and can be viewed as consisting of a Kalman-Bucy filter along with the on-line computation of the solution of the associated Riccati equation, which is driven by the observations. The usefulness of these results is illustrated via an example concerning the detection of an actuator failure in a rigid body rotational control system.

Willsky, A. S.↗
NASA NTRS1974

Estimation and detection of signals in multiplicative noise

We define a class of detection-estimation problems on matrix Lie groups in which the observation noise is multiplicative in nature. By examining the differential versions of the hypotheses, which are bilinear, we are able to derive the relevant likelihood ratio formula and the associated optimal estimation equations for the signal given the observations and the assumption that the signal is present. These estimation equations are of interest in their own right, in that they represent a finite-dimensional optimal solution to a nonlinear estimation problem and consist of a Kalman-Bucy filter along with the on-line computation of the solution of the associated Riccati equation, which is driven by the observations. The usefulness of these results is illustrated via an example concerning the detection of an actuator failure in a rigid-body rotational control system.

Willsky, A. S.↗
NASA NTRS1977

Digital flight control systems

The design of stable feedback control laws for sampled-data systems with variable rate sampling was investigated. These types of sampled-data systems arise naturally in digital flight control systems which use digital actuators where it is desirable to decrease the number of control computer output commands in order to save wear and tear of the associated equipment. The design of aircraft control systems which are optimally tolerant of sensor and actuator failures was also studied. Detection of the failed sensor or actuator must be resolved and if the estimate of the state is used in the control law, then it is also desirable to have an estimator which will give the optimal state estimate even under the failed conditions.

Caglayan, A. K.↗
NASA NTRS1987

Intelligent fault-tolerant controllers

A system with fault tolerant controls is one that can detect, isolate, and estimate failures and perform necessary control reconfiguration based on this new information. Artificial intelligence (AI) is concerned with semantic processing, and it has evolved to include the topics of expert systems and machine learning. This research represents an attempt to apply AI to fault tolerant controls, hence, the name intelligent fault tolerant control (IFTC). A generic solution to the problem is sought, providing a system based on logic in addition to analytical tools, and offering machine learning capabilities. The advantages are that redundant system specific algorithms are no longer needed, that reasonableness is used to quickly choose the correct control strategy, and that the system can adapt to new situations by learning about its effects on system dynamics.

Huang, Chien Y.↗
NASA NTRS1987

Monitoring robot actions for error detection and recovery

Reliability is a serious problem in computer controlled robot systems. Although robots serve successfully in relatively simple applications such as painting and spot welding, their potential in areas such as automated assembly is hampered by programming problems. A program for assembling parts may be logically correct, execute correctly on a simulator, and even execute correctly on a robot most of the time, yet still fail unexpectedly in the face of real world uncertainties. Recovery from such errors is far more complicated than recovery from simple controller errors, since even expected errors can often manifest themselves in unexpected ways. Here, a novel approach is presented for improving robot reliability. Instead of anticipating errors, researchers use knowledge-based programming techniques so that the robot can autonomously exploit knowledge about its task and environment to detect and recover from failures. They describe preliminary experiment of a system that they designed and constructed.

Gini, M.↗
NASA NTRS1993

An optical motion measuring system for laterally oscillated fatigue tests

This paper describes an optical system developed for materials testing laboratories at NASA Langley Research Center (LaRC) for high resolution monitoring of the transverse displacement and angular rotation of a test specimen installed in an axial-tension bending machine (ATB) during fatigue tests. It consists of a small laser, optics, a motorized mirror, three photodiodes, electronic detection and counting circuits, a data acquisition system, and a personal computer. A 3-inch by 5-inch rectangular plate attached to the upper grip of the test machine serves as a target base for the optical system. The personal computer automates the fatigue test procedure, controls data acquisition, performs data reduction, and provides user displays. The data acquisition system also monitors signals from up to 16 strain gages mounted on the test specimen. The motion measuring system is designed to continuously monitor and correlate the amplitude of the oscillatory motion with the strain gage signals in order to detect the onset of failure of the composite test specimen. A prototype system has been developed and tested which exceeds the design specifications of +/- 0.01 inch displacement accuracy, and +/- 0.25 deg angular accuracy at a sampling rate of 100 samples per second.

Tripp, John S.↗
NASA NTRS1994

Instrumentation for In-Flight SSME Rocket Engine Plume Spectroscopy

This paper describes instrumentation that is under development for an in-flight demonstration of a plume spectroscopy system on the space shuttle main engine. The instrumentation consists of a nozzle mounted optical probe for observation of the plume, and a spectrometer for identification and quantification of plume content. This instrumentation, which is intended for use as a diagnostic tool to detect wear and incipient failure in rocket engines, will be validated by a hardware demonstration on the Technology Test Bed engine at the Marshall Space Flight Center.

Madzsar, George C.↗
NASA NTRS1994

Duration versus brightness of gamma-ray bursts: Comparisons between SIGNE and BATSE

We analyze duration and brightness distributions of both the SIGNE Venera 13 and 14 and Burst and Transient Source Experiment (BATSE) gamma-ray burst databases. Choosing T(sub 50) as a measure of the burst duration and using both 64 and 1024 ms peak count rates, we search for correlations between duration, peak brightness, and the ratio V identically equals C(sub 64)/C(sub 1024), proposed as a measure of variability by Lamb, Graziani, & Smith. The duration histogram for SIGNE shows a long-duration peak that is consistent with BATSE, but does not exhibit the short population, instead appearing flat below 0.6 s; the difference is presumably caused by the failure of SIGNE to detect the short, faint bursts that were observed by BATSE. Estimating the instantaneous brightness by C(sub 64), we find that SIGNE confirms the BATSE result that the long and short bursts have similar maximum instantaneous brightnesses. Scatterplots between duration, brightness, and V are consistent for both databases; we show that SIGNE confirms the BATSE observation that there is a lack of bursts that are both bright over 1024 ms and contain a short, bright spike.

Kargatis, V. E.↗
NASA NTRS1994

Software-Implemented Fault Tolerance in Communications Systems

Software-implemented fault tolerance (SIFT) is used in many computer-based command, control, and communications (C(3)) systems to provide the nearly continuous availability that they require. In the communications subsystem of Space Station Alpha, SIFT algorithms are used to detect and recover from failures in the data and command link between the Station and its ground support. The paper presents a review of these algorithms and discusses how such techniques can be applied to similar systems found in applications such as manufacturing control, military communications, and programmable devices such as pacemakers. With support from the Tracking and Communication Division of NASA's Johnson Space Center, researchers at the University of Wyoming are developing a testbed for evaluating the effectiveness of these algorithms prior to their deployment. This testbed will be capable of simulating a variety of C(3) system failures and recording the response of the Space Station SIFT algorithms to these failures. The design of this testbed and the applicability of the approach in other environments is described.

Gantenbein, Rex E.↗