scholarly journals Robotized line-scan thermography combined with a new compressed sensing technology for investigating a painting on canvas artwork

2019 ◽  
Author(s):  
Hai Zhang ◽  
Mingli Zhang ◽  
Stefano Sfarra ◽  
Ahmad Osman ◽  
Clemente Ibarra-Castanedo ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Line Scan ◽  
Sensing Technology ◽  
Painting On Canvas ◽  
Line Scan Thermography

Constructing the Seismograms of Future Earthquakes in Yunnan, China, Using Compressed Sensing

2020 ◽  
Vol 92 (1) ◽  
pp. 261-274
Author(s):  
Jie Zhang ◽  
Huiyu Zhu ◽  
Siwei Yu ◽  
Jianwei Ma
Keyword(s):  
Compressed Sensing ◽  
Active Fault ◽  
Regional Scale ◽  
Focal Mechanism Solution ◽  
Total Output ◽  
Detailed Knowledge ◽  
Large Dataset ◽  
Sensing Technology ◽  
Data Driven Approach ◽  
Using Data

Abstract The ability to calculate the seismogram of an earthquake at a local or regional scale is critical but challenging for many seismological studies because detailed knowledge about the 3D heterogeneities in the Earth’s subsurface, although essential, is often insufficient. Here, we present an application of compressed sensing technology that can help predict the seismograms of earthquakes at any position using data from past events randomly distributed in the same area in Jinggu County, Yunnan, China. This first data-driven approach for calculating seismograms generates a large dataset in 3D with a volume encompassing an active fault zone. The input number of earthquakes comprises only 1.27% of the total output events. We use the output data to create a database intended to find the best-matching waveform of a new event by applying an earthquake search engine, which instantly reveals the hypocenter and focal-mechanism solution.

Reconstruction of Slice Image from Solid Rocket Motor Skiagrams Based on Compressed Sensing Algorithm

2013 ◽  
Vol 321-324 ◽  
pp. 1035-1040
Author(s):  
Zhi Gao Xu ◽  
Chao Ning ◽  
Jing Ma ◽  
Xiang Bin Li
Keyword(s):  
Compressed Sensing ◽  
Rocket Motor ◽  
Reconstructed Image ◽  
Solid Rocket Motor ◽  
Sensing Technology ◽  
Radiographic Interpretation ◽  
Solid Rocket ◽  
Slice Image ◽  
Algebraic Reconstruction

A reconstruction program of slice image based on SolidRocket Motor (SRM) skiagrams is put forward to overcome the deficiency of artificial radiographic interpretation. The algebraic reconstruction algorithmbased on compressed sensing technology is designed. The influence of radiographic interval angle and skiagram sizes on reconstructed slice image is studied. Radiographic interval angle has a great impact on the quality of the reconstructed image. Slender defects are not sensitive to changes in the length of the skiagram, but circular defects are sensitive to changes in the length of the skiagram. The reconstruction tests of model SRM skiagrams show that the sizes and locations of the debonded defects can be easily ascertained and the efficiency of radiographic interpretation can be greatly improved.

A Simple Deterministic 0-1 Measurement Matrix for Robotic Embedded Vision Compressed Sensing

2013 ◽  
Vol 433-435 ◽  
pp. 257-260
Author(s):  
Ji Zhong Liu ◽  
Ru Yuan Ma ◽  
Yuan Bin Mo ◽  
Ming Liang Jin
Keyword(s):  
Compressed Sensing ◽  
Processing Speed ◽  
Vision System ◽  
Image Data ◽  
Measurement Matrix ◽  
Embedded Vision ◽  
Sensing Technology ◽  
Embedded Vision System ◽  
And Performance ◽  
Reconstruction Time

Embedded environmental vision is a key issue for robotics. However, the image data is large, which usually will seriously affect the system processing speed and performance. Aiming at the feasibility and the real-time performance of robotic embedded vision system, by combining the up-to-date compressed sensing technology, a novel wavelet sparsity based simple deterministic 0-1 measurement matrix (0-1SDMM) is designed. The simulation results in matlab environment show that the 0-1SDMM has better performance than traditional Gaussian matrix in reconstruction result and reconstruction time. It provides an important reference for the future robotic embedded vision system.

scholarly journals Dynamic Line Scan Thermography Optimisation Using Response Surfaces Implemented on PVC Flat Bottom Hole Plates

2021 ◽  
Vol 11 (4) ◽  
pp. 1538 ◽  
Author(s):  
Simon Verspeek ◽  
Jona Gladines ◽  
Bart Ribbens ◽  
Xavier Maldague ◽  
Gunther Steenackers
Keyword(s):  
Material Properties ◽  
Optimal Parameter ◽  
Response Surfaces ◽  
Flat Bottom ◽  
Line Scan ◽  
Size And Shape ◽  
Set Up ◽  
Detail Loss ◽  
Optimal Set ◽  
Line Scan Thermography

Nowadays, performing dynamic line scan thermography (DLST) is very challenging, and therefore an expert is needed in order to predict the optimal set-up parameters. The parameters are mostly dependent on the material properties of the object to be inspected, but there are also correlations between the parameters themselves. The interrelationship is not always evident even for someone skilled in the art. Therefore, optimisation using response surface can give more insights in the interconnections between parameters, but also between the material properties and the variables. Performing inspections using an optimised parameter set will result in high contrast thermograms showing the size and shape of the defect accurately. Using response surfaces to predict the optimal parameter set enables to perform fast measurements without the need of extensive testing to find adequate measurement parameters. Differing from the optimal parameters will result in contrast loss or detail loss of the size and shape of the detected defect.

Noisy Signal Processing Research based on Compressed Sensing Technology

2016 ◽  
Vol 3 (3) ◽  
pp. 489
Author(s):  
Guojun Qin ◽  
Jingfang Wang
Keyword(s):  
Fourier Transform ◽  
Compressed Sensing ◽  
Fast Fourier Transform ◽  
Speech Enhancement ◽  
Speech Compression ◽  
Noisy Signal ◽  
Sensing Technology ◽  
Observation Matrix ◽  
Separable Approximation ◽  
Enhancement Method

<span lang="EN-US">Compressed sensing (CS) is a kind of sampling method based on signal sparse property, it can effectively extract the signal which was contained in the message. In this study, a new noise speech enhancement method was proposed based on CS process.  </span><span lang="EN-US">V</span><span lang="EN-US">oice sparsity </span><span lang="EN-US">is </span><span lang="EN-US">use</span><span lang="EN-US">d to this a</span><span lang="EN-US">lgorithm in the discrete fast Fourier transform (Fast Fourier transform, FFT),</span><span lang="EN-US">and observation matrix is  designed</span><span lang="EN-US"> in </span><span lang="EN-US">complex domain,  and the noisy speech compression measurement and de-noising are made by soft threshold,  and the speech signal is sparsely reconstructed</span><span lang="EN-US"> and </span><span lang="EN-US">restore</span><span lang="EN-US">d</span><span lang="EN-US"> by separable approximation (Sparse Reconstruction by Separable Approximation, SpaRSA) algorithm, speech enhancement</span><span lang="EN-US">is improved.  Experimental results show that the denoising compression reconstruction is </span><span lang="EN-US">made for </span><span lang="EN-US">the noisy signal in  the algorithm, SNR margin is improved greatly, and the background noise can be more effectively suppressed .</span>

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