Autonomous mobile lock-in thermography system for detecting and quantifying voids in liquefied natural gas cargo tank second barrier

2016 ◽  
Vol 16 (3) ◽  
pp. 276-290 ◽  
Author(s):  
Sangmin Lee ◽  
Hyung Jin Lim ◽  
Hoon Sohn ◽  
Wonjun Yun ◽  
Eunha Song
Keyword(s):  
Image Processing ◽  
Natural Gas ◽  
Liquefied Natural Gas ◽  
Measurement Unit ◽  
Inspection System ◽  
Void Size ◽  
Thermal Images ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Lock In

In this study, an autonomous mobile inspection system that can detect and quantify hidden voids in a secondary barrier (triplex layer) of a liquefied natural gas cargo tank is developed using lock-in thermography. The triplex layer is the secondary barrier to prevent gas leaks from a Mark III–type membrane liquefied natural gas carrier cargo tank and consists of three sub-layers: a flexible secondary barrier, a bonding layer, and a rigid secondary barrier. The proposed mobile inspection system consists of a lock-in thermography measurement unit, a mobile inspection unit, and image processing algorithms. First, thermal images are obtained using the lock-in thermography unit as the mobile inspection system maneuvers over triplex layers. Second, the raw thermal images are processed by several image processing techniques to compensate for non-uniform heating, eliminate noise components, and disregard trivial voids in accordance with the current inspection guideline. Third, the void size is more precisely quantified using an empirical mapping function that relates the void size estimated in the previous step to that measured by an independent X-ray test. The contributions of this study include the following: (1) an autonomous mobile inspection system is developed for real-time inspection of the triplex during its installation, significantly saving the inspection cost and time; (2) a suite of image processing techniques is developed, overcoming shortcomings of the existing thermography non-destructive testing techniques; and (3) the sizes as well as the locations of the hidden voids are quantified with high accuracy, reliability, and fast inspection speed.

scholarly journals Smart Dye Inspection System in Textile Industry

2020 ◽  
Vol 8 (6) ◽  
pp. 5061-5063
Keyword(s):  
Image Processing ◽  
Reference Material ◽  
Textile Industry ◽  
High Accuracy ◽  
Inspection System ◽  
Manual Operation ◽  
Image Processing Techniques ◽  
Manual Inspection ◽  
Processing Techniques

Inspection on the dyed material in the textile industry is facing a challenging task owing to the accurate measurement of the dye concentration added. Currently manual inspection is done. It consumes more time and less accurate. The proposed work provides a solution to above problem. The image of reference material (cloth) is captured and the features are extracted using image processing techniques. The color concentration of both the reference material and the test fabric is compared. If the dye concentration of the test fabric matches with the reference material, then it is a perfect dyed cloth whereas for mismatched samples, the concentration is to be adjusted is displayed. This smart dyeing inspection system reduces the manual operation and saves time and results in high accuracy.

Image Processing Techniques in Thermal and Non-thermal Images

2021 ◽  
pp. 533-544
Author(s):  
Ushus S. Kumar ◽  
Judy Simon ◽  
Reshma P. Vengaloor ◽  
M. Aarthi Elaveini
Keyword(s):  
Image Processing ◽  
Thermal Images ◽  
Image Processing Techniques ◽  
Processing Techniques

Three-Dimensional Structure of Rotavirus-Fab Complex

1990 ◽  
Vol 48 (1) ◽  
pp. 238-239
Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu
Keyword(s):  
Image Processing ◽  
Smooth Surface ◽  
Three Dimensional ◽  
Outer Shell ◽  
Dimensional Structure ◽  
Structural Studies ◽  
Cell Penetration ◽  
Electron Cryomicroscopy ◽  
Image Processing Techniques ◽  
Processing Techniques

Rotaviruses are spherical, double-shelled particles. They have been identified as a major cause of infantile gastroenteritis worldwide. In our earlier studies we determined the three-dimensional structures of double-and single-shelled simian rotavirus embedded in vitreous ice using electron cryomicroscopy and image processing techniques to a resolution of 40Å. A distinctive feature of the rotavirus structure is the presence of 132 large channels spanning across both the shells at all 5- and 6-coordinated positions of a T=13ℓ icosahedral lattice. The outer shell has 60 spikes emanating from its relatively smooth surface. The inner shell, in contrast, exhibits a bristly surface made of 260 morphological units at all local and strict 3-fold axes (Fig.l).The outer shell of rotavirus is made up of two proteins, VP4 and VP7. VP7, a glycoprotein and a neutralization antigen, is the major component. VP4 has been implicated in several important functions such as cell penetration, hemagglutination, neutralization and virulence. From our earlier studies we had proposed that the spikes correspond to VP4 and the rest of the surface is composed of VP7. Our recent structural studies, using the same techniques, with monoclonal antibodies specific to VP4 have established that surface spikes are made up of VP4.

A Survey on Detection and Classification of Brain Tumor Using Image Processing Techniques

2020 ◽  
pp. 967-973
Author(s):  
V. Deepika ◽  
T. Rajasenbagam
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Soft Tissues ◽  
Tumor Detection ◽  
Tumor Classification ◽  
Normal Brain ◽  
Image Processing Techniques ◽  
Normal Brain Function ◽  
Processing Techniques ◽  
The Brain

A brain tumor is an uncontrolled growth of abnormal brain tissue that can interfere with normal brain function. Although various methods have been developed for brain tumor classification, tumor detection and multiclass classification remain challenging due to the complex characteristics of the brain tumor. Brain tumor detection and classification are one of the most challenging and time-consuming tasks in the processing of medical images. MRI (Magnetic Resonance Imaging) is a visual imaging technique, which provides a information about the soft tissues of the human body, which helps identify the brain tumor. Proper diagnosis can prevent a patient's health to some extent. This paper presents a review of various detection and classification methods for brain tumor classification using image processing techniques.

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