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Digital graph element represents two-state devices. It can be used in modeling mechanical stops, backlash, and other discontinuities that occur whenever subsystems are connected or disconnected.
Instrument data systems consist of a microprocessor, 3K bytes of Read Only Memory and 3K bytes of Random Access Memory. It interfaces with the spacecraft data bus through an isolated user interface with a direct memory access bus adaptor, and/or parallel data from instrument devices such as registers, buffers, analog to digital converters, multiplexers, and solid state sensors. These data systems support the spacecraft hardware and software communication protocol, decode and process instrument commands, generate continuous instrument operating modes, control the instrument mechanisms, acquire, process, format, and output instrument science data.
A system consisting of a single charge coupled device (CCD) video camera, computer controlled video digitizer, and software to automate the measurement was developed to measure the location of bullet holes in targets at the International Shooters Development Fund (ISDF)/NASA Ballistics Tunnel. The camera/digitizer system is a crucial component of a highly instrumented indoor 50 meter rifle range which is being constructed to support development of wind resistant, ultra match ammunition. The system was designed to take data rapidly (10 sec between shoots) and automatically with little operator intervention. The system description, measurement concept, and procedure are presented along with laboratory tests of repeatability and bias error. The long term (1 hour) repeatability of the system was found to be 4 microns (one standard deviation) at the target and the bias error was found to be less than 50 microns. An analysis of potential errors and a technique for calibration of the system are presented.
The purpose of this research program is to design, build and test (in cooperation with NASA personnel from the NASA Langley Research Center) neural controllers for two different small air-gap magnetic suspension systems. The general objective of the program is to study neural network architectures for the purpose of control in an experimental setting and to demonstrate the feasibility of the concept. The specific objectives of the research program are: (1) to demonstrate through simulation and experimentation the feasibility of using neural controllers to stabilize a nonlinear magnetic suspension system; (2) to investigate through simulation and experimentation the performance of neural controllers designs under various types of parametric and nonparametric uncertainty; (3) to investigate through simulation and experimentation various types of neural architectures for real-time control with respect to performance and complexity; and (4) to benchmark in an experimental setting the performance of neural controllers against other types of existing linear and nonlinear compensator designs. To date, the first one-dimensional, small air-gap magnetic suspension system has been built, tested and delivered to the NASA Langley Research Center. The device is currently being stabilized with a digital linear phase-lead controller. The neural controller hardware is under construction. Two different neural network paradigms are under consideration, one based on hidden layer feedforward networks trained via back propagation and one based on using Gaussian radial basis functions trained by analytical methods related to stability conditions. Some advanced nonlinear control algorithms using feedback linearization and sliding mode control are in simulation studies.
The techniques used to acquire, reduce, and analyze dynamic deformation measurements of an aeroelastic semispan wind tunnel model are presented. Single-camera, single-view video photogrammetry (also referred to as videogrammetric model deformation, or VMD) was used to determine dynamic aeroelastic deformation of the semispan 'Models for Aeroelastic Validation Research Involving Computation' (MAVRIC) model in the Transonic Dynamics Tunnel at the NASA Langley Research Center. Dynamic deformation was determined from optical retroreflective tape targets at five semispan locations located on the wing from the root to the tip. Digitized video images from a charge coupled device (CCD) camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. Videogrammetric dynamic data were acquired at a 60-Hz rate for time records of up to 6 seconds during portions of this flutter/Limit Cycle Oscillation (LCO) test at Mach numbers from 0.3 to 0.96. Spectral analysis of the deformation data is used to identify dominant frequencies in the wing motion. The dynamic data will be used to separate aerodynamic and structural effects and to provide time history deflection data for Computational Aeroelasticity code evaluation and validation.
A method of processing the digitized output of a charge-coupled device (CCD) image detector has been devised to enable reduction of the error in computed centroid of the image of a point source of light. The method involves model-based estimation of, and correction for, the contributions of bias and noise to the image data. The method could be used to advantage in any of a variety of applications in which there are requirements for measuring precise locations of, and/or precisely aiming optical instruments toward, point light sources. In the present method, prior to normal operations of the CCD, one measures the point-spread function (PSF) of the telescope or other optical system used to project images on the CCD. The PSF is used to construct a database of spot models representing the nominal CCD pixel outputs for a point light source projected onto the CCD at various positions incremented by small fractions of a pixel.
Radar at JPL and worldwide is enjoying a period of unprecedented development. JPL's science-driven program focuses on exploiting commercially available components to build new technologies to meet NASA's science goals. Investments in onboard-processing, advanced digital systems, and efficient high-power devices, point to a new generation of high-performance scientific SAR systems in the US. Partnerships are a key strategy for US missions in the coming decade
Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties). To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.
Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties).To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.
Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by accidental improper relay settings or deliberate malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that their performance falls within expectations. Relays that fail to isolate a fault or trip when there is no system disturbance can be flagged for settings review in situations where this behavior may not have been noticed due to manual restoration or backup protection operations. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by identifying fault events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.
Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by improper relay settings or malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that they act and perform as expected. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.
A poster for the Early Career Poster Session. Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by improper relay settings or malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that they act and perform as expected. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.
Measurement processes, data and analysis are provided to address the concern for Wireless Local Area Network devices and two-way radios to cause electromagnetic interference to aircraft navigation radio systems. A radiated emission measurement process is developed and spurious radiated emissions from various devices are characterized using reverberation chambers. Spurious radiated emissions in aircraft radio frequency bands from several wireless network devices are compared with baseline emissions from standard computer laptops and personal digital assistants. In addition, spurious radiated emission data in aircraft radio frequency bands from seven pairs of two-way radios are provided, A description of the measurement process, device modes of operation and the measurement results are reported. Aircraft interference path loss measurements were conducted on four Boeing 747 and Boeing 737 aircraft for several aircraft radio systems. The measurement approach is described and the path loss results are compared with existing data from reference documents, standards, and NASA partnerships. In-band on-channel interference thresholds are compiled from an existing reference document. Using these data, a risk assessment is provided for interference from wireless network devices and two-way radios to aircraft systems, including Localizer, Glideslope, Very High Frequency Omnidirectional Range, Microwave Landing System and Global Positioning System. The report compares the interference risks associated with emissions from wireless network devices and two-way radios against standard laptops and personal digital assistants. Existing receiver interference threshold references are identified as to require more data for better interference risk assessments.
A description is given of a video kinesimeter, a device for the automatic real-time collection of kinematic and dynamic data. Based on the detection of a single bright spot by three TV cameras, the system provides automatic real-time recording of three-dimensional position and force data. It comprises three cameras, two incandescent lights, a voltage comparator circuit, a central control unit, and a mass storage device. The control unit determines the signal threshold for each camera before testing, sequences the lights, synchronizes and analyzes the scan voltages from the three cameras, digitizes force from a dynamometer, and codes the data for transmission to a floppy disk for recording. Two of the three cameras face each other along the 'X' axis; the third camera, which faces the center of the line between the first two, defines the 'Y' axis. An image from the 'Y' camera and either 'X' camera is necessary for determining the three-dimensional coordinates of the point.
The annular suspension and pointing system (ASPS) a payload auxiliary pointing device of the space shuttle is briefly described along with the function of the digital controller. The equations of motion of a simplified plan planar model of the ASPS are derived. Results of computer simulations are discussed.
A prototype data acquisition system is described. The device characteristics, its performance and the system aspects connected to the integration of the data acquisition system into the space simulator instrumentation and environment are discussed. The data acquisition system has a modular architecture and manifold configuration capability. The input characteristics feature high resolution and accuracy/stability for the measurement of low level (thermocouple originated) analog signals, even in the presence of high common mode and S/N figures. The output is serial digital, compatible with ESA data handling standards. The device is designed to be installed in particularly hostile environments, such as that of a solar simulator.
A frequent complaint in the computer oriented trade journals is that current hardware technology is progressing so quickly that software developers cannot keep up. A example of this phenomenon can be seen in the field of microcomputer graphics. To exploit the advantages of new mechanisms of information storage and retrieval, new approaches must be made towards incorporating existing programs as well as developing entirely new applications. A particular area of need is the correlation of discrete image elements to textural information. The interactive digital video (IDV) interface embodies a new concept in software design which addresses these needs. The IDV interface is a patented device and language independent process for identifying image features on a digital video display and which allows a number of different processes to be keyed to that identification. Its capabilities include the correlation of discrete image elements to relevant text information and the correlation of these image features to other images as well as to program control mechanisms. Sophisticated interrelationships can be set up between images, text, and program control mechanisms.
Abstract The recent emergence of novel computational devices, such as quantum computers, coherent Ising machines, and digital annealers presents new opportunities for hardware-accelerated hybrid optimization algorithms. Unfortunately, demonstrations of unquestionable performance gains leveraging novel hardware platforms have faced significant obstacles. One key challenge is understanding the algorithmic properties that distinguish such devices from established optimization approaches. Through the careful design of contrived optimization tasks, this work provides new insights into the computation properties of quantum annealing and suggests that this model has the potential to quickly identify the structure of high-quality solutions. A meticulous comparison to a variety of algorithms spanning both complete and local search suggests that quantum annealing’s performance on the proposed optimization tasks is distinct. This result provides new insights into the time scales and types of optimization problems where quantum annealing has the potential to provide notable performance gains over established optimization algorithms and suggests the development of hybrid algorithms that combine the best features of quantum annealing and state-of-the-art classical approaches.