Results for “Digital data acquisition” — Page 29

NASA NTRS2007

Guaranteeing Pointing Performance of the SDO Sun-Pointing Controllers in Light of Nonlinear Effects

The Solar Dynamics Observatory (SDO) mission is the first Space Weather Research Network mission, part of NASA s Living With a Star program.1 This program seeks to understand the changing Sun and its effects on the Solar System, life, and society. To this end, the SDO spacecraft will carry three Sun-observing instruments to geosynchronous orbit: Helioseismic and Magnetic Imager (HMI), led by Stanford University; Atmospheric Imaging Assembly (AIA), led by Lockheed Martin Space and Astrophysics Laboratory; and Extreme Ultraviolet Variability Experiment (EVE), led by the University of Colorado. Links describing the instruments in detail may be found through the SDO web site.2 The basic mission goals are to observe the Sun for a very high percentage of the 5-year mission (10-year goal) with long stretches of uninterrupted observations and with constant, high-data-rate transmission to a dedicated ground station. These goals guided the design of the spacecraft bus that will carry and service the three-instrument payload. At the time of this publication, the SDO spacecraft bus is well into the integration and testing phase at the NASA Goddard Space Flight Center (GSFC). A three-axis stabilized attitude control system (ACS) is needed both to point at the Sun accurately and to keep the roll about the Sun vector correctly positioned. The ACS has four reaction wheel modes and 2 thruster actuated modes. More details about the ACS in general and the control modes in particular can be found in Refs. [3-6]. All four of SDO s wheel-actuated control modes involve Sun-pointing controllers, as might be expected from such a mission. Science mode, during which most science data is collected, uses specialized guide telescopes to point accurately at the Sun. Inertial mode has two sub-modes, one tracks a Sun-referenced target orientation, and another maintains an absolute (star-referenced) target orientation, that both employ a Kalman filter to process data from a digital Sun sensor and two star trackers. However, this paper is concerned only with the other two modes: Safe Hold (SH) and Sun Acquisition (SA).

Starin, Scott R.↗

DOE OSTI2016

Control and data acquisition upgrades for NSTX-U

The extensive NSTX Upgrade (NSTX-U) Project includes major components which allow a doubling of the toroidal field strength to 1 T, of the Neutral Beam heating power to 12 MW, and the plasma current to 2 MA, and substantial structural enhancements to withstand the increased electromagnetic loads. The maximum pulse length will go from 1.5 to 5 s. The larger and more complex forces on the coils will be protected by a Digital Coil Protection System, which requires demanding real-time data input rates, calculations and responses. The amount of conventional digitized data for a given pulse is expected to increase from 2.5 to 5 GB per second of pulse. 2-D Fast Camera data is expected to go from 2.5 GB/pulse to 10, and another 2 GB/pulse is expected from new IR cameras. Our network capacity will be increased by a factor of 10, with 10 Gb/s fibers used for the major trunks. 32-core Linux systems will be used for several functions, including between-shot data processing, MDSplus data serving, between-shot EFIT analysis, real-time processing, and for a new capability, between-shot TRANSP. As a result, improvements to the MDSplus events subsystem will be made through the use of both UDP and TCP/IP based methods and the addition of a dedicated “event server”.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2000

Improving Cloud Detection in Satellite Images of Coral Reef Environments Using Space Shuttle Photographs and High-Definition Television

Coral reefs worldwide are suffering from severe and rapid degradation (Bryant et A, 1998; Hoegh-Guldberg, 1999). Quick, consistent, large-scale assessment is required to assess and monitor their status (e.g., USDOC/NOAA NESDIS et al., 1999). On-going systematic collection of high resolution digital satellite data will exhaustively complement the relatively small number of SPOT, Landsat 4-5, and IRS scenes acquired for coral reefs the last 20 years. The workhorse for current image acquisition is the Landsat 7 ETM+ Long Term Acquisition Plan (Gasch et al. 2000). Coral reefs are encountered in tropical areas and cloud contamination in satellite images is frequently a problem (Benner and Curry 1998), despite new automated techniques of cloud cover avoidance (Gasch and Campana 2000). Fusion of multidate acquisitions is a classical solution to solve the cloud problems. Though elegant, this solution is costly since multiple images must be purchased for one location; the cost may be prohibitive for institutions in developing countries. There are other difficulties associated with fusing multidate images as well. For example, water quality or surface state can significantly change through time in coral reef areas making the bathymetric processing of a mosaiced image strenuous. Therefore, another strategy must be selected to detect clouds and improve coral reefs mapping. Other supplemental data could be helpful and cost-effective for distinguishing clouds and generating the best possible reef maps in the shortest amount of time. Photographs taken from the 1960s to the present from the Space Shuttle and other human-occupied spacecraft are one under-used source of alternative multitemporal data (Lulla et al. 1996). Nearly 400,000 photographs have been acquired during this period, an estimated 28,000 of these taken to date are of potential value for reef remote sensing (Robinson et al. 2000a). The photographic images can be digitized into three bands (red, green and blue) and processed for various applications (e.g., Benner and Curry 1998, Nedeltchev 1999, Glasser and Lulla 2000, Robinson et al. 2000c, Webb et al, in press).

Andrefeouet, Serge↗

DOE OSTI2020

Requirements Document for a Replacement Data Acquisition System

A flight vehicle is in the developmental stages. While in development flight testing is required by both the manufacturer and customer to rate design performance. The performance of the vehicle must fulfill the agreed upon requirements. Testing of a flight vehicle during operation requires various sensors in order to record and monitor performance for evaluation. A Data Acquisition System (DAQ) is needed in order to control and capture data from various sensors placed throughout the vehicle during flight. This DAQ will receive the analog data from the suite of sensors and convert them to a digital signal that can be transmitted to a recording station where the data will later be analyzed by test experts. Some of the key features to be included in the DAQ will be a self-check operation to verify the health of all sensors including the DAQ. The DAQ will also have the capability to store sensor calibration data files loaded during assembly and transmit those files to the recording station during flight. Breakthroughs in new technologies has allowed for higher resolution recording systems and faster sampling rates. Improved sensor data using a new Data Acquisition System (DAQ) can provide important answers to questions discovered during the last few flight tests. These questions arose when the flight system expressed unexpected behaviors. Having the capability of the new DAQ in flight tests would allow for more high-fidelity data to be captured from the system during flight tests and ultimately reducing the number of required flight test. Reducing the number of flight tests also reduce developmental cost and schedule.

42 ENGINEERING↗

DOE OSTI2015

WE-AB-BRB-09: Real Time In Vivo Scintillating Fiber Array Detector for Medical LINACS

Purpose: An in vivo transmission scintillation fiber detector was developed to monitor patient treatment in real time for the enhancement of patient safety and treatment accuracy. The detector system is capable of monitoring each pulse from a medical LINAC during treatment to determine the dose delivered as treatment progresses. Methods: The detector system consists of 60 parallel scintillating fibers coupled to fast data processing optoelectronics that can monitor the beam fluence in real time. Each 2.5mm{sup 2} square fiber is aligned with an MLC leaf pair and is long enough to capture a 40cm field. The fibers are embedded within a water equivalent polymer substrate that is secured in the LINAC accessory tray. The fibers are coupled to high speed photosensors and front end amplifiers that filter noise and pass each pulse to a high speed analog-to-digital converter. The system components are capable of detecting pulse repetition times shorter than what is delivered by a medical LINAC to ensure true real time data acquisition. Results: The system was able to capture and record the signal from each linac pulse and display the information in real time with no pulse pile up. It was found that the fiber array attenuates 2.65% of the beam which can easily be compensated for in treatment planning. The fibers responded linearly with dose, are independent of clinical beam energies, and are independent of dose rate. Calibration of the system was performed as a function of beam energy, beam size, dose rate, and monitor units to optimize beam fluence error detection. Conclusion: The detector system presented provides true real time in vivo beam monitoring to enhance patient safety and treatment delivery accuracy. Furthermore, the detector can be used for current patient specific QA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Digital Twin for Chemical Science (DTCS) v0.01

Directly visualizing the trajectories of chemistry can unravel novel insights into the behavior of catalysts, gas phase reactions, photo-induced dynamics, and building blocks for quantum information processing. The ability of explicitly identifying, tracking, and tagging the exchange of matter, hence the annihilation and creation of new chemical species, can be best realized through a close coupling of theory and experiment. While the synchrotron-based characterization facilities propelled rapidly in its hardware, providing higher brightness, better resolution, and more precision, the software infrastructure is lagging. We developed DTCS (Digital Twin for Chemical Science) v.01, a central platform that faithfully mimics advanced instrumentations in Scientific User Facilities, by solving a variety of technical challenges in data acquisition, analysis, and model-driven interpretation. Rooted in physics and accelerated by AI, we validated this concept by direct comparison with precise experimental X-ray Photoelectron Spectroscopy (XPS) observations using a ubiquitous metal-water interfacial scenario, i.e., Ag/H2O as our main narrative. The DTCS v.01 input mirrors how the bench chemists work, with the output directly linked to the end station computer, thereby providing a user-friendly, knowledge-driven, and accessible user experience with mechanistic insights standardized in a way that are ready to be published, versioned, and transferred flexibly.

Qian, Jin↗

DOE OSTI2015

CRADA: Data Acquisition and Tomographic Software Development

Dr. Raymond R. Raylman, Professor and Vice Chair for Research, Radiology Department at WVU was the Principal Investigator for the project. The Jefferson Lab partner on this project was the Radiation Detector and Imaging Group in the Physics Division, led by Dr. Drew Weisenberger who was the coordinator of the project execution and the chief contact with WVU. The responsibility of Jefferson Lab was to facilitate optimization of data acquisition software, conversion of JLab Fortran iterative positron emission mammography computer code to C++ and to act as a computer code repository. During the two year project interactions and exchange of information was directed by Dr. Raylman and Dr. Wesienberger. WVU provided the expertise that allowed JLab to continue development of the current JLab data acquisition software referred to as JDAQ. JDAQ is a highly flexible Java language based data acquisition tool that helps to minimize software induced dead-time while maintaining the highest possible data rates from a JLab built FPGA based analog-to-digital convertor (ADC). JDAQ interfaces directly with the FPGA based multi-channel ADCs. Using JDAQ it is possible process data from a number of different detector types such as the PET systems at WVU. Because of the inherent flexibility of our processing software, we are also able adjust detector readout parameters during operation to provide the best possible data presentation and calibration parameters. To accommodate the high rate nature of PET detector systems JDAQ was designed to be scalable across an Ethernet network as well as for multi-cpu computer systems, and it also has the capability to synchronize many ADCs connected to multiple computers. During the project WVU will provided iterative reconstruction algorithm expertise and Fortran programming assistance to facilitate the conversion to C++ of a JLab developed Fortran positron emission mammography (PEM) reconstruction code. Also WVU provided acceptance testing of the new C++ based PEM reconstruction code. The PEM code is a maximization (MLEM) image reconstruction program that created images from the list-mode data acquired from the PET system.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1977

A comparison of photointerpretive and digital production methods for four key remote sensing-based information products

This paper evaluates the costs of producing four remote sensing-based information products: timber volume estimate tables, Level II land use/land cover maps, soil maps, and vegetative cover maps. Two production methods for each product are evaluated, one is based on digital processing of satellite data, and the other on conventional photointerpretation of aircraft data. For each product, a comparison is conducted of the two strategies' production costs (including data acquisition, 'ground truthing', interpretation, compilation, and printing charges) and their performance (as measured by accuracy and timeliness). Each of the production methods reviewed has been demonstrated - either operationally or experimentally - and the costs, timeliness and other performance estimates presented are based on observations made in practice. The results show that for these products, satellite-based production results in significant cost and timeliness improvements at the cost of a loss in accuracy.

Eastwood, L. F., Jr.↗

NASA NTRS1983

Interactive Data-Collection And Display Program With Debugging

INFORM program designed to aid assembly language programers of SEL 810B computers in working with scaled-integer applications. INFORM was developed to meet needs of engineers designing real-time digital controls using SEL 810B where time and hardware constraints make use of integer arithmetic and scaled integers necessary. Package includes auxiliary routines that add dynamic data acquisition and high-speed dynamic display to INFORM capabilities.

Cwynar, D. S.↗

NASA NTRS1981

University/industry collaboration in remote sensing education

A graduate level course covering the development and structure of geographical information systems and the acquisition and processing of LANDSAT data for input to these systems is described. A portion of the course was devoted to hands-on classification of LANDSAT digital tapes utilizing both university and private industry processing systems. This industry/university collaboration was extremely successful and resulted in a high quality course. It gave the students an excellent experience in working in a real-world client/consultant relationship undertaken to accomplish a specific task. There were two key factors in the success of the collaboration. First, there was a very careful product definition and advance meetings between the University faculty and the company personnel to be involved. Second, the students were not taken into the industrial facility until late in the course, after they had a reasonable knowledge of the physical bases of remote sensing, the concept of spectral signatures, and the fundamentals of pattern analysis.

Ragan, R. M.↗

NASA NTRS2009

R4SA for Controlling Robots

The R4SA GUI mentioned in the immediately preceding article is a userfriendly interface for controlling one or more robot(s). This GUI makes it possible to perform meaningful real-time field experiments and research in robotics at an unmatched level of fidelity, within minutes of setup. It provides such powerful graphing modes as that of a digitizing oscilloscope that displays up to 250 variables at rates between 1 and 200 Hz. This GUI can be configured as multiple intuitive interfaces for acquisition of data, command, and control to enable rapid testing of subsystems or an entire robot system while simultaneously performing analysis of data. The R4SA software establishes an intuitive component-based design environment that can be easily reconfigured for any robotic platform by creating or editing setup configuration files. The R4SA GUI enables event-driven and conditional sequencing similar to those of Mars Exploration Rover (MER) operations. It has been certified as part of the MER ground support equipment and, therefore, is allowed to be utilized in conjunction with MER flight hardware. The R4SA GUI could also be adapted to use in embedded computing systems, other than that of the MER, for commanding and real-time analysis of data.

Aghazarian, Hrand↗

NASA NTRS2017

The Mars Science Laboratory Curiosity Rover Mastcam Instruments: Preflight and In-Flight Calibration, Validation, and Data Archiving

The NASA Curiosity rover Mast Camera (Mastcam) system is a pair of fixed-focal length, multispectral, color CCD imagers mounted approximately 2 m above the surface on the rover's remote sensing mast, along with associated electronics and an onboard calibration target. The left Mastcam (M-34) has a 34 mm focal length, an instantaneous field of view (IFOV) of 0.22 mrad, and a FOV of 20 deg × 15 deg over the full 1648 × 1200 pixel span of its Kodak KAI-2020 CCD. The right Mastcam (M-100) has a 100 mm focal length, an IFOV of 0.074 mrad, and a FOV of 6.8 deg × 5.1 deg using the same detector. The cameras are separated by 24.2 cm on the mast, allowing stereo images to be obtained at the resolution of the M-34 camera. Each camera has an eight-position filter wheel, enabling it to take Bayer pattern red, green, and blue (RGB) 'true color' images, multispectral images in nine additional bands spanning approximately 400-1100 nm, and images of the Sun in two colors through neutral density-coated filters. An associated Digital Electronics Assembly provides command and data interfaces to the rover, 8 Gb of image storage per camera, 11 bit to 8 bit companding, JPEG compression, and acquisition of high-definition video. Here we describe the preflight and in-flight calibration of Mastcam images, the ways that they are being archived in the NASA Planetary Data System, and the ways that calibration refinements are being developed as the investigation progresses on Mars. We also provide some examples of data sets and analyses that help to validate the accuracy and precision of the calibration.

MSL Mastcam; quantitative multispectral↗

NASA NTRS1973

Photometric and polarimetric mapping of water turbidity and water depth

A Digital Photometric Mapper (DPM) was used in the Fall of 1971 in an airborne survey of New York and Boston area waters to acquire photometric, spectral and polarimetric data. The object of this study is to analyze these data with quantitative computer processing techniques to assess the potential of the DPM in the measurement and regional mapping of water turbidity and depth. These techniques have been developed and an operational potential has been demonstrated. More emphasis is placed at this time on the methodology of data acquisition, analysis and display than on the quantity of data. The results illustrate the type, quantity and format of information that could be generated operationally with the DPM-type sensor characterized by high photometric stability and fast, accurate digital output. The prototype, single-channel DPM is suggested as a unique research tool for a number of new applications. For the operational mapping of water turbidity and depth, the merits of a multichannel DPM coupled with a laser system are stressed.

Halajian, J.↗

NASA NTRS2006

High-Performance Scanning Acousto-Ultrasonic System

A high-performance scanning acousto-ultrasonic system, now undergoing development, is designed to afford enhanced capabilities for imaging microstructural features, including flaws, inside plate specimens of materials. The system is expected to be especially helpful in analyzing defects that contribute to failures in polymer- and ceramic-matrix composite materials, which are difficult to characterize by conventional scanning ultrasonic techniques and other conventional nondestructive testing techniques. Selected aspects of the acousto-ultrasonic method have been described in several NASA Tech Briefs articles in recent years. Summarizing briefly: The acousto-ultrasonic method involves the use of an apparatus like the one depicted in the figure (or an apparatus of similar functionality). Pulses are excited at one location on a surface of a plate specimen by use of a broadband transmitting ultrasonic transducer. The stress waves associated with these pulses propagate along the specimen to a receiving transducer at a different location on the same surface. Along the way, the stress waves interact with the microstructure and flaws present between the transducers. The received signal is analyzed to evaluate the microstructure and flaws. The specific variant of the acousto-ultrasonic method implemented in the present developmental system goes beyond the basic principle described above to include the following major additional features: Computer-controlled motorized translation stages are used to automatically position the transducers at specified locations. Scanning is performed in the sense that the measurement, data-acquisition, and data-analysis processes are repeated at different specified transducer locations in an array that spans the specimen surface (or a specified portion of the surface). A pneumatic actuator with a load cell is used to apply a controlled contact force. In analyzing the measurement data for each pair of transducer locations in the scan, the total (multimode) acousto-ultrasonic response of the specimen is utilized. The analysis is performed by custom software that extracts parameters of signals in the time and frequency domains. The computer hardware and software provide both real-time and postscan processing and display options. For example, oscilloscope displays of waveforms and power spectral densities are available in real time. Images can be computed while scanning continues. Signals can be digitally preprocessed and/or post-processed by filtering, windowing, time-segmenting, and running-waveform-averaging algorithms. In addition, the software affords options for off-line simulation of the waveform-data-acquisition and scanning processes. In tests, the system has been shown to be capable of characterizing microstructural changes and defects in SiC/SiC and C/SiC ceramic-matrix composites. Delaminations, variations in density, microstructural changes attributable to infiltration by silicon, and crack-space indications (defined in the next sentence) have been revealed in images formed from several time- and frequency-domain parameters of scanning acousto-ultrasonic signals. The crack-space indications were image features that were not revealed by other nondestructive testing methods and are so named because they turned out to mark locations where cracking eventually occurred.

Roth, Don↗

DOE OSTI2016

WE-G-209-00: Identifying Image Artifacts, Their Causes, and How to Fix Them

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-G-209-01: Digital Radiography

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-G-209-02: CT

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-G-209-03: PET

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗