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At least 379 records · Page 21

Simulation of Detecting Damage in Composite Stiffened Panel Using Lamb Waves

Lamb wave damage detection in a composite stiffened panel is simulated by performing explicit transient dynamic finite element analyses and using signal imaging techniques. This virtual test process does not need to use real structures, actuators/sensors, or laboratory equipment. Quasi-isotropic laminates are used for the stiffened panels. Two types of damage are studied. One type is a damage in the skin bay and the other type is a debond between the stiffener flange and the skin. Innovative approaches for identifying the damage location and imaging the damage were developed. The damage location is identified by finding the intersection of the damage locus and the path of the time reversal wave packet re-emitted from the sensor nodes. The damage locus is a circle that envelops the potential damage locations. Its center is at the actuator location and its radius is computed by multiplying the group velocity by the time of flight to damage. To create a damage image for estimating the size of damage, a group of nodes in the neighborhood of the damage location is identified for applying an image condition. The image condition, computed at a finite element node, is the zero-lag cross-correlation (ZLCC) of the time-reversed incident wave signal and the time reversal wave signal from the sensor nodes. This damage imaging process is computationally efficient since only the ZLCC values of a small amount of nodes in the neighborhood of the identified damage location are computed instead of those of the full model.

Wang, John T.↗

Study of one- and two-dimensional filtering and deconvolution algorithms for a streaming array computer

The development of vector processing computers of the streaming array architectures has made possible a dramatic decrease in the time required for the solution of problems, i.e., for those algorithms which readily lend themselves to sequential operations on long vectors. There has concurrently been rapid growth in the applications of the techniques generally known as mathematical digital filtering, also called signal analysis, digital signal processing, time series analysis, and digital image processing. The best known applications of these techniques is to seismic data and two-dimensional images, data types consisting of very large collections of numbers. A major limitation for these cases is the size and speed of the computer available. Therefore, a move to the streaming array architecture can result in marked improvement in the data analysis techniques which may be employed.

Ioup, G. E.↗

Optical distributed sensing and computation for a proposed flexible beam experiment

A new technology is being developed that supports distributed sensing and computation wherein crystal mediums are used with real-time holography to gather images that contain vibration and instantaneous geometry data for a spacecraft. Optical computation techniques are employed to process the image data and to compute commands to actuators located on the spacecraft. This paper presents an integrated sensor/processor design for an experiment to demonstrate this technology. A performance estimate for the design is presented in terms of the optical spatial bandwidth of the imaging system, as opposed to the temporal bandwidth. The advantages of an integrated optical sensor/processor relative to control of large spacecraft are addressed.

Welch, S. S.↗

Electroluminescence Imaging: A Quantitative Characterization Technique to Measure Dust Occlusion of Solar Cells

Electroluminescence (EL) imaging is a qualitative characterization technique that is typically used to identify cracks, corrosion, and other defects in solar cells. It consists of imaging a cell under forward bias, where the solar cell emits photons due to radiative electron-hole pair recombination. Over the past few years, our team has expanded this into a quantitative technique with the help of image processing. We have primarily used this method to investigate lunar dust occlusion of solar cells and arrays. Lunar dust accumulation on solar cells is a major concern because it directly limits light accessible to the cell, decreasing power output. Many teams are working to develop dust mitigation technology to protect these arrays on the surface of the Moon, but thoroughly characterizing their efficacy is important to ensure their success prior to launch. Here, we present EL as a quantitative characterization technique to observe dust coverage on solar cells that, when coupled with IV performance measurements, can offer unique insights into how dust coverage impacts power output. Quantitative electroluminescence imaging works by running EL images through an image processing script that first grayscales the image then plots a histogram of the brightness of each pixel. On its own, it does not offer much insight into a solar cell’s performance. However, when comparing images to a baseline pristine, undamaged, or uncoated solar cell, it can quickly provide information about the impacts of surface contaminants or damage to the cell. Here, we present a case study where quantitative EL is used to measure the efficacy of dust mitigation technology for flexible solar arrays and discuss the lessons learned about dust mitigation, testing with lunar simulant, and this characterization technique.

photovoltaics↗

Estimating Doppler Shifts for Synthetic-Aperture Radar

Quality of synthetic-aperture-radar (SAR) imagery enhanced by pair of signal-processing techniques that compensate for relative motion between target and vehicle. Combining vehicle trajectory data with radar-parameter and raw image data, techniques generate Doppler estimates for use in constructing fully processed images.

Curlander, J. C.↗

Separation of topographic and intrinsic backscatter variations in biscopic radar images: A magic airbrush

Shaded-relief maps portraying landforms as they would appear in the absence of variations in the intrinsic brightness of the surface are a venerable and extremely useful tool in planetary geology. Such maps have traditionally been produced by a highly labor intensive manual process. Skilled cartographer-artists develop detailed mental images of landforms by meticulous scrutiny of all available data, and are able to use an airbrush and electric eraser to draw these images on a map. This process becomes increasingly time-consuming or even impossible if - as is true for radar data in general and Magellan data in particular - the effects on image brightness of varying scattering properties greatly outweigh those of slope variations. Because of the difficulty of interpreting relief in the Magellan images, the airbrush technique is being used only to remove obvious artifacts from low-resolution, shaded-relief images computed digitally from altimetric data. A surprisingly simple digital-processing technique that can be applied to pairs of radar images to produce shaded-relief-like results at the full image resolution is described. These shaded-relief images can be used not only as base maps, but to improve the accuracy of quantitative topographic mapping by radarclinometry and stereoanalysis.

Kirk, R. L.↗

Image-Driven Hybrid Structural Analysis Based on Continuum Point Cloud Method with Boundary Capturing Technique

Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure. The captured edge profiles are transformed into essential boundary conditions. This allows the construction of a strongly formulated boundary value problem (BVP), classified as the Dirichlet problem. Capturing boundary conditions from the digital image is novel, although a similar approach was applied to the point cloud data. It was shown that the CPCM is more efficient in this hybrid simulation framework than the weak-form-based numerical schemes. Unlike the finite element method (FEM), it can avoid aligning boundary nodes with regression points. A three-point bending test of a rubber beam was simulated to validate the developed technique. The simulation results were benchmarked against numerical results by ANSYS and various relevant numerical schemes. The technique can effectively solve the Dirichlet-type BVP, yielding accurate deformation, stress, and strain values across the entire problem domain when employing a linear strain model and increasing the number of CPCM nodes. In addition, comparative analysis with conventional displacement tracking techniques verifies the developed technique’s robustness. The proposed technique effectively circumvents the inherent limitations of traditional monitoring methods resulting from the reliance on physical gauges or target markers so that a robust and non-contact solution for remote structural health monitoring in real-scale infrastructures can be provided, even in unfavorable experimental environments.

Chemistry↗

Thermographic characterization of stress during crack growth

A full-field-thermographic technique for imaging stress patterns in dynamically loaded structures using general purpose IR imaging and image processing hardware is described. The inspection technique is based on the thermoelastic effect. A simple geometry is examined, and the experimentally determined values for the stress invariant are shown to be consistent with theoretical and numerical calculations. The application of full-field-thermographic measurement would ensure that the observed stress field has a common sampling period, thus allowing the observation of rapidly occurring stress anomalies such as the propagation of a fatigue crack. Fatigue crack propagation in two consecutive thermoelastic stress images from an aluminum sample is shown.

Cramer, K. E.↗

Parameter Estimation in Atmospheric Data Sets

In this study the structure tensor technique is used to estimate dynamical parameters in atmospheric data sets. The structure tensor is a common tool for estimating motion in image sequences. This technique can be extended to estimate other dynamical parameters such as diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. As a test scenario this technique will be applied to modeled dust data. In this case vertically integrated dust concentrations were used to derive wind information. Those results can be compared to the wind vector fields which served as input to the model. Based on this analysis, a method to compute atmospheric data parameter fields will be presented. .

Wenig, Mark↗

Flow velocity measurements by image processing of optically activated tracers

A computerized flow visualization technique capable of quantifying the flow field automatically has been developed. This technique uses afterglowing effect of optically activated phosphorescent particles to retrieve vectorial information on each trace. By using this information, in conjunction with computer image processing, the flow field of a free surface transient vortex was investigated.

Gharib, M.↗

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Effective monitoring of global water resources is increasingly critical due to climate change and population growth. Advancements in remote sensing technology, specifically in spatial, spectral, and temporal resolutions, are revolutionizing water resource monitoring, leading to more frequent and high-quality surface water extent maps using various techniques such as traditional image processing and machine learning algorithms. However, satellite imagery datasets contain trade-offs that result in inconsistencies in performance, such as disparities in measurement principles between optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) sensors and differences in spatial and spectral resolutions among optical sensors. Therefore, developing accurate and robust surface water mapping solutions requires independent validations from multiple datasets to identify potential biases within the imagery and algorithms. However, high-quality validation datasets are expensive to build, and few contain information on water resources. For this purpose, we introduce a globally sampled, high-spatial-resolution dataset labeled using 3 m PlanetScope imagery. Our surface water extent dataset comprises 100 images, each with a size of 1024×1024 pixels, which were sampled using a stratified random sampling strategy covering all 14 biomes. We highlighted urban and rural regions, lakes, and rivers, including braided rivers and coastal regions. We evaluated two surface water extent mapping methods using our dataset – Dynamic World, based on Sentinel-2, and the NASA IMPACT model, based on Sentinel-1. Dynamic World achieved a mean intersection over union (IoU) of 72.16 % and F1 score of 79.70 %, while the NASA IMPACT model had a mean IoU of 57.61 % and F1 score of 65.79 %. Performance varied substantially across biomes, highlighting the importance of evaluating models on diverse landscapes to assess their generalizability and robustness. Our dataset can be used to analyze satellite products and methods, providing insights into their advantages and drawbacks. Our dataset offers a unique tool for analyzing satellite products, aiding the development of more accurate and robust surface water monitoring solutions. The dataset can be accessed via https://doi.org/10.25739/03nt-4f29.

54 ENVIRONMENTAL SCIENCES↗

Digital techniques for processing Landsat imagery

An overview of the basic techniques used to process Landsat images with a digital computer, and the VICAR image processing software developed at JPL and available to users through the NASA sponsored COSMIC computer program distribution center is presented. Examples of subjective processing performed to improve the information display for the human observer, such as contrast enhancement, pseudocolor display and band rationing, and of quantitative processing using mathematical models, such as classification based on multispectral signatures of different areas within a given scene and geometric transformation of imagery into standard mapping projections are given. Examples are illustrated by Landsat scenes of the Andes mountains and Altyn-Tagh fault zone in China before and after contrast enhancement and classification of land use in Portland, Oregon. The VICAR image processing software system which consists of a language translator that simplifies execution of image processing programs and provides a general purpose format so that imagery from a variety of sources can be processed by the same basic set of general applications programs is described.

Green, W. B.↗

Textbooks and technical references for remote sensing

A selective bibliography is presented which cites 89 textbooks, monographs, and articles covering introductory and advanced remote sensing techniques, photointerpretation, photogrammetry, and image processing.

Rudd, R. D.↗

A perspective view of the plane mixing layer

A three-dimensional model of the plane mixing layer is constructed by applying digital image processing and computer graphic techniques to laser fluorescent motion pictures of its transversal sections. A system of streamwise vortex pairs is shown to exist on top of the classical spanwise eddies. Its influence on mixing is examined.

Jimenez, J.↗

Terrestrial imaging spectroscopy

Recent advances in imaging spectroscopy for remote sensing applications are discussed, reviewing the results of recent investigations. The advantages offered by the higher spectral resolution of imaging spectroscopy relative to scanners such as Landsat MSS and TM are explained; the design and performance of the Airborne Imaging Spectrometer (Vane et al., 1984) are described and illustrated with drawings, photographs, and sample images; data processing and analysis techniques are outlined; and applications to geological and botanical research are considered.

Vane, Gregg↗

A hardware implementation of a relaxation algorithm to segment images

Relaxation labelling is a mathematical technique frequently applied in image processing algorithms. In particular, it is extensively used for the purpose of segmenting images. The paper presents a hardware implementation of a segmentation algorithm, for images consisting of two regions, based on relaxation labelling. The algorithm determines, for each pixel, the probability that it should be labelled as belonging to a particular region, for all regions in the image. The label probabilities (labellings) of every pixel are iteratively updated, based on those of the pixel's neighbors, until they converge. The pixel is then assigned to the region correspondent to the maximum label probability. The system consists of a control unit and of a pipeline of segmentation stages. Each segmentation stage emulates in the hardware an iteration of the relaxation algorithm. The design of the segmentation stage is based on commercially available digital signal processing integrated circuits. Multiple iterations are accomplished by stringing stages together or by looping the output of a stage, or string of stages, to its input. The system interfaces with a generic host computer. Given the modularity of the architecture, performance can be enhanced by merely adding segmentation stages.

Loda, Antonio G.↗

Incorporation of shuttle CCT parameters in computer simulation models

Computer simulations of shuttle missions have become increasingly important during recent years. The complexity of mission planning for satellite launch and repair operations which usually involve EVA has led to the need for accurate visibility and access studies. The PLAID modeling package used in the Man-Systems Division at Johnson currently has the necessary capabilities for such studies. In addition, the modeling package is used for spatial location and orientation of shuttle components for film overlay studies such as the current investigation of the hydrogen leaks found in the shuttle flight. However, there are a number of differences between the simulation studies and actual mission viewing. These include image blur caused by the finite resolution of the CCT monitors in the shuttle and signal noise from the video tubes of the cameras. During the course of this investigation the shuttle CCT camera and monitor parameters are incorporated into the existing PLAID framework. These parameters are specific for certain camera/lens combinations and the SNR characteristics of these combinations are included in the noise models. The monitor resolution is incorporated using a Gaussian spread function such as that found in the screen phosphors in the shuttle monitors. Another difference between the traditional PLAID generated images and actual mission viewing lies in the lack of shadows and reflections of light from surfaces. Ray tracing of the scene explicitly includes the lighting and material characteristics of surfaces. The results of some preliminary studies using ray tracing techniques for the image generation process combined with the camera and monitor effects are also reported.

Huntsberger, Terry↗