Development of Infrared Microscopy for Measuring Asperity Contact Temperatures

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Julian Le Rouzic ◽  
Tom Reddyhoff
Keyword(s):  
Spatial Resolution ◽  
Heat Dissipation ◽  
Background Radiation ◽  
Rough Surfaces ◽  
Super Resolution ◽  
Research Area ◽  
Mapping Technique ◽  
Asperity Contact ◽  
Temperature Mapping ◽  
Current Limit

Surface temperature measurements within sliding contacts are useful since interfacial heat dissipation is closely linked to tribological behavior. One of the most powerful techniques for such measurements is in-contact temperature mapping whereby a sliding contact is located beneath an infrared microscope. In this approach, one of the specimens must be transparent to infrared and coated such that radiation components can be distinguished and isolated from background values. Despite its effectiveness, a number of practical constraints prevent this technique from being applied to rough surfaces—a research area where temperature maps could provide much needed two-dimension input data to inform mixed and boundary friction models. The research described in this paper is aimed at improving the infrared temperature mapping technique in terms of validity, robustness, and spatial resolution, so that measurements of rough surfaces contacts can be made. First, Planck's law is applied in order to validate the use of surface coating as a means of removing background radiation. Second, a refined method of calibration is put forward and tested, which negates the need for a soft aluminum coating and hence enables rough surfaces to be measured. Finally, the use of super-resolution algorithms is assessed in order extend spatial resolution beyond the current limit of 6 μm.

A Low Electron Voltage Approach to Increase Spatial Resolution of Temperature Mapping in Thermal Scanning Electron Microscopy

2013 ◽  
Vol 1525 ◽  
Author(s):  
Xiaowei Wu ◽  
Robert Hull
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Spatial Resolution ◽  
Electron Backscatter Diffraction ◽  
Mapping Technique ◽  
Thermal Diffuse Scattering ◽  
Temperature Mapping ◽  
Energy Incident ◽  
Backscatter Diffraction ◽  
Scanning Electron

ABSTRACTThermal scanning electron microscopy is a new temperature mapping technique based on thermal diffuse scattering in electron backscatter diffraction in a scanning electron microscope. It provides both nano-scale resolution and far-field non-contact temperature mapping capabilities no other methods can adequately combine. While a calculated spatial resolution of less than 100 nm has already been realized using 20 keV electrons, lower energy incident electrons should enable still higher spatial resolution (even down to 10 nm). In this paper, the feasibility of this approach is examined.

scholarly journals Super-resolution time-resolved imaging using computational sensor fusion

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. Callenberg ◽  
A. Lyons ◽  
D. den Brok ◽  
A. Fatima ◽  
A. Turpin ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Single Photon ◽  
Super Resolution ◽  
Numerical Data ◽  
Data Cube ◽  
Fluorescence Lifetime Imaging ◽  
Time Resolved ◽  
Temporal Precision

AbstractImaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fluorescence lifetime imaging. However, compromises that sacrifice, for example, spatial resolution at the expense of temporal resolution are often required, in particular when the full 3-dimensional data cube is required in short acquisition times. We introduce a sensor fusion approach that combines data having low-spatial resolution but high temporal precision gathered with a single-photon-avalanche-diode (SPAD) array with data that has high spatial but no temporal resolution, such as that acquired with a standard CMOS camera. Our method, based on blurring the image on the SPAD array and computational sensor fusion, reconstructs time-resolved images at significantly higher spatial resolution than the SPAD input, upsampling numerical data by a factor $$12 \times 12$$ 12 × 12 , and demonstrating up to $$4 \times 4$$ 4 × 4 upsampling of experimental data. We demonstrate the technique for both LIDAR applications and FLIM of fluorescent cancer cells. This technique paves the way to high spatial resolution SPAD imaging or, equivalently, FLIM imaging with conventional microscopes at frame rates accelerated by more than an order of magnitude.

scholarly journals Deriving VIIRS High-Spatial Resolution Water Property Data over Coastal and Inland Waters Using Deep Convolutional Neural Network

2021 ◽  
Vol 13 (10) ◽  
pp. 1944
Author(s):  
Xiaoming Liu ◽  
Menghua Wang
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Ocean Color ◽  
Super Resolution ◽  
Inland Waters ◽  
Coastal Oceans ◽  
Chl A ◽  
Color Data

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been a reliable source of ocean color data products, including five moderate (M) bands and one imagery (I) band normalized water-leaving radiance spectra nLw(λ). The spatial resolutions of the M-band and I-band nLw(λ) are 750 m and 375 m, respectively. With the technique of convolutional neural network (CNN), the M-band nLw(λ) imagery can be super-resolved from 750 m to 375 m spatial resolution by leveraging the high spatial resolution features of I1-band nLw(λ) data. However, it is also important to enhance the spatial resolution of VIIRS-derived chlorophyll-a (Chl-a) concentration and the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), as well as other biological and biogeochemical products. In this study, we describe our effort to derive high-resolution Kd(490) and Chl-a data based on super-resolved nLw(λ) images at the VIIRS five M-bands. To improve the network performance over extremely turbid coastal oceans and inland waters, the networks are retrained with a training dataset including ocean color data from the Bohai Sea, Baltic Sea, and La Plata River Estuary, covering water types from clear open oceans to moderately turbid and highly turbid waters. The evaluation results show that the super-resolved Kd(490) image is much sharper than the original one, and has more detailed fine spatial structures. A similar enhancement of finer structures is also found in the super-resolved Chl-a images. Chl-a filaments are much sharper and thinner in the super-resolved image, and some of the very fine spatial features that are not shown in the original images appear in the super-resolved Chl-a imageries. The networks are also applied to four other coastal and inland water regions. The results show that super-resolution occurs mainly on pixels of Chl-a and Kd(490) features, especially on the feature edges and locations with a large spatial gradient. The biases between the original M-band images and super-resolved high-resolution images are small for both Chl-a and Kd(490) in moderately to extremely turbid coastal oceans and inland waters, indicating that the super-resolution process does not change the mean values of the original images.

Super-resolution plasmonic imaging via scattering saturation STED

2021 ◽  
Vol 57 (28) ◽  
pp. 3492-3495
Author(s):  
Zhaoshuai Gao ◽  
Pei Wu ◽  
Lixin Yin ◽  
Bin Kang ◽  
Hong-Yuan Chen ◽  
...  
Keyword(s):  
Gold Nanoparticles ◽  
Spatial Resolution ◽  
Super Resolution ◽  
Plasmonic Imaging

Super-resolution plasmonic scattering imaging was realized with a 65 nm spatial resolution on 50 nm gold nanoparticles.

scholarly journals Super Resolution Digital Image Correlation (SR-DIC): an Alternative to Image Stitching at High Magnifications

2021 ◽  
Author(s):  
R. S. Hansen ◽  
D. W. Waldram ◽  
T. Q. Thai ◽  
R. B. Berke
Keyword(s):  
High Resolution ◽  
Digital Image Correlation ◽  
Spatial Resolution ◽  
Digital Image ◽  
Super Resolution ◽  
Image Correlation ◽  
Low Resolution ◽  
Strain Measurements ◽  
Resolution Image ◽  
High Resolution Image

Abstract Background High-resolution Digital Image Correlation (DIC) measurements have previously been produced by stitching of neighboring images, which often requires short working distances. Separately, the image processing community has developed super resolution (SR) imaging techniques, which improve resolution by combining multiple overlapping images. Objective This work investigates the novel pairing of super resolution with digital image correlation, as an alternative method to produce high-resolution full-field strain measurements. Methods First, an image reconstruction test is performed, comparing the ability of three previously published SR algorithms to replicate a high-resolution image. Second, an applied translation is compared against DIC measurement using both low- and super-resolution images. Third, a ring sample is mechanically deformed and DIC strain measurements from low- and super-resolution images are compared. Results SR measurements show improvements compared to low-resolution images, although they do not perfectly replicate the high-resolution image. SR-DIC demonstrates reduced error and improved confidence in measuring rigid body translation when compared to low resolution alternatives, and it also shows improvement in spatial resolution for strain measurements of ring deformation. Conclusions Super resolution imaging can be effectively paired with Digital Image Correlation, offering improved spatial resolution, reduced error, and increased measurement confidence.

Approximate Macroscale Constitutive Relations Using a Finite Element Based Constitutive Equations for Microscale Contact

2008 ◽  
Author(s):  
Ali Sepehri ◽  
Kambiz Farhang
Keyword(s):  
Finite Element ◽  
Contact Force ◽  
Rough Surfaces ◽  
Constitutive Relations ◽  
Cumulative Effect ◽  
Element Model ◽  
Tangential Component ◽  
Total Force ◽  
Asperity Contact ◽  
Elastic Plastic

Three dimensional elastic-plastic contact of two nominally flat rough surfaces is considered. Equations governing the shoulder-shoulder contact of asperities are derived based on the asperity-asperity constitutive relations from a finite element model of their elastic-plastic interaction. Shoulder-shoulder asperity contact yields a slanted contact force consisting of both tangential (parallel to mean plane) and normal components. Multiscale modeling of the elastic-plastic rough surface contact is presented in which asperity-level FE-based constitutive relations are statistically summed to obtain total force in the normal and tangential direction. The equations derived are in the form of integral functions and provide expectation of contact force components between two rough surfaces. An analytical fusion technique is developed to combine the piecewise asperity level constitutive relations. This is shown to yield upon statistical summation the cumulative effect resulting in the contact force between two rough surfaces with two components, one in the normal direction and a half-plane tangential component.

SISSI Project: A Feasibility Study for a Super Resolved Compressive Sensing Multispectral Imager in the Medium Infrared

2021 ◽  
Vol 8 (1) ◽  
pp. 28
Author(s):  
Cinzia Lastri ◽  
Gabriele Amato ◽  
Massimo Baldi ◽  
Tiziano Bianchi ◽  
Maria Fabrizia Buongiorno ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Compressive Sensing ◽  
Feasibility Study ◽  
Spatial Resolution ◽  
Spatial Light Modulator ◽  
Super Resolution ◽  
Earth Observation ◽  
Light Modulator ◽  
The Core ◽  
Multispectral Imager

This paper describes the activities related to a feasibility study for an Earth observation optical payload, operating in the medium infrared, based on super-resolution and compressive sensing techniques. The presented activities are running in the framework of the ASI project SISSI, aiming to improve ground spatial resolution and mitigate saturation/blooming effects. The core of the payload is a spatial light modulator (SLM): a bidimensional array of micromirrors electronically actuated. Thanks to compressive sensing approach, the proposed payload eliminates the compression board, saving mass, memory and energy consumption.

scholarly journals Spatio-Temporal Super-Resolution Land Cover Mapping Based on Fuzzy C-Means Clustering

2018 ◽  
Vol 10 (8) ◽  
pp. 1212 ◽  
Author(s):  
Xiaohong Yang ◽  
Zhong Xie ◽  
Feng Ling ◽  
Xiaodong Li ◽  
Yihang Zhang ◽  
...  
Keyword(s):  
Land Cover ◽  
Spatial Pattern ◽  
Spatial Resolution ◽  
Super Resolution ◽  
Land Cover Mapping ◽  
Fuzzy C Means Clustering ◽  
Land Cover Map ◽  
Spatio Temporal ◽  
Fine Resolution ◽  
Land Cover Maps

Super-resolution land cover mapping (SRM) is a method that aims to generate land cover maps with fine spatial resolutions from the original coarse spatial resolution remotely sensed image. The accuracy of the resultant land cover map produced by existing SRM methods is often limited by the errors of fraction images and the uncertainty of spatial pattern models. To address these limitations in this study, we proposed a fuzzy c-means clustering (FCM)-based spatio-temporal SRM (FCM_STSRM) model that combines the spectral, spatial, and temporal information into a single objective function. The spectral term is constructed with the FCM criterion, the spatial term is constructed with the maximal spatial dependence principle, and the temporal term is characterized by the land cover transition probabilities in the bitemporal land cover maps. The performance of the proposed FCM_STSRM method is assessed using data simulated from the National Land Cover Database dataset and real Landsat images. Results of the two experiments show that the proposed FCM_STSRM method can decrease the influence of fraction errors by directly using the original images as the input and the spatial pattern uncertainty by inheriting land cover information from the existing fine resolution land cover map. Compared with the hard classification and FCM_SRM method applied to mono-temporal images, the proposed FCM_STSRM method produced fine resolution land cover maps with high accuracy, thus showing the efficiency and potential of the novel approach for producing fine spatial resolution maps from coarse resolution remotely sensed images.

On the Static-Kinetic Friction Transition in Dry Contact of Rough Surfaces

2011 ◽  
Author(s):  
K. Farhang ◽  
D. Segalman ◽  
M. Starr
Keyword(s):  
Large Scale ◽  
Rough Surfaces ◽  
Tangential Force ◽  
Static Friction ◽  
Partial Slip ◽  
Small Scale ◽  
Asperity Contact ◽  
Kinetic Friction ◽  
Tangential Load ◽  
Asperity Contacts

This paper shows that the Mindlin problem involving two spheres in contact under the action of oscillating tangential force can lead to the account of static-kinetic friction transition. In Mindlin’s problem two spheres experience partial slip as a result of application of oscillating tangential load. When the problem is extended to multi-sphere contact, i.e. two rough surfaces, the application of tangential oscillating load results in partial slip for some asperity contacts while others experience full slip. Increase in the amplitude of the oscillating tangential force results in more contacts experiencing full slip, thereby decreasing the number of contacts in parial slip. Constitutive relation proposed by Mindlin at small scale, governing asperity interaction, is used to obtain the large scale slip function through a statistical summation of asperity scale events. The slip function establishes the fraction of asperity contact in full slip. The complement of the slip parameter is a fraction of asperities in partial slip. Through slip function it is shown that it is possible to define a slip condition for the entire surface. The derivation of the slip function allows the account of transition between static friction and kinetic friction.

scholarly journals Downscaling of GRACE-Derived Groundwater Storage Based on the Random Forest Model

2019 ◽  
Vol 11 (24) ◽  
pp. 2979 ◽  
Author(s):  
Li Chen ◽  
Qisheng He ◽  
Kun Liu ◽  
Jinyang Li ◽  
Chenlin Jing
Keyword(s):  
Random Forest ◽  
Spatial Resolution ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Water Storage ◽  
Research Area ◽  
Groundwater Storage ◽  
Coarse Spatial Resolution ◽  
Long Time ◽  
Local Water

Groundwater is an important part of water storage and one of the important sources of agricultural irrigation, urban living, and industrial water use. The recent launch of Gravity Recovery and Climate Experiment (GRACE) Satellite has provided a new way for studying large-scale water storage. The application of GRACE in local water resources has been greatly limited because of the coarse spatial resolution, and low temporal resolution. Therefore, it is of great significance to improve the spatial resolution of groundwater storage for regional water management. Based on the method of random forest (RF), this study combined six hydrological variables, including precipitation, evapotranspiration, runoff, soil moisture, snow water equivalent, and canopy water to conduct downscaling study, aiming at downscaling the resolution of the total water storage and groundwater storage from 1° (110 km) and to 0.25° (approximately 25 km). The results showed that, from the perspective of long time series, the prediction results of the RF model are ideal in the whole research area and the observations wells area. From the perspective of space, the detailed changes of water storage could be captured in greater detail after downscaling. The verification results show that, on the monthly scale and annual scale, the correlation between the downscaling results and the observation wells is 0.78 and 0.94, respectively, and they both reach the confidence level of 0.01. Therefore, the RF downscaling model has great potential for predicting groundwater storage.

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