scholarly journals Strain Measurements by Full-Field Optical Techniques

2020 ◽  
Author(s):  
Rasoul Rashidifar ◽  
Hamid Reza Eslami
Keyword(s):  
Quality Assurance ◽  
Industrial Applications ◽  
Field Methods ◽  
Full Field ◽  
Strain Measurements ◽  
Strain Concentration ◽  
Stamping Die ◽  
Development Cycle ◽  
Computer Aided ◽  
Speed Up

A weak position and possibly leads to make a defected material and production. Localized strain concentration is becoming very important in the area of quality assurance. Recently, there are many research that researcher proposed using Computer-Aided-Engineering (CAE) tools to reduce the number of prototype builds and to speed up the development cycle. In this paper, there are some literature about researches that conducted in this field. The capabilities as well as the limitations for industrial applications are investigated. An application of this method is demonstrated on a stamping die to validate a FEM results. Full-field methods of strain measurements are very broad and many number of these techniques are using and can be widely categorized to two groups as Geometrical methods and Interferometric methods.

A review of automated methods for the collection and analysis of photoelastic data

1998 ◽  
Vol 33 (2) ◽  
pp. 75-91 ◽  
Author(s):  
A Ajovalasit ◽  
S Barone ◽  
G Petrucci
Keyword(s):  
Experimental Stress ◽  
Field Methods ◽  
Spectral Content ◽  
Full Field ◽  
Experimental Stress Analysis ◽  
Phase Stepping ◽  
Speed Up ◽  
Photoelastic Data ◽  
The Fourier Transform ◽  
Automated Methods

Photoelasticity is one of the most widely used full-field methods for experimental stress analysis. However, the collection of photoelastic parameters can be a long and tedious process. The advent of automated photoelastic systems has allowed the experimentalists to speed up the rate of analysis and to perform more complex investigations. This paper provides a survey of recent methods of automated photoelasticity developed in the last 20 years, i.e. methods of the fringe centres, half-fringe photoelasticity, phase-stepping photoelasticity, methods based on the Fourier transform, spectral content analysis (SCA) and RGB (red, green, blue) photoelasticity.

Strain measurements in the nanometer range in a particulate composite using computer-aided moiré

2003 ◽  
Vol 43 (3) ◽  
pp. 341-347 ◽  
Author(s):  
C. A. Sciammarella ◽  
F. M. Sciammarella ◽  
T. Kim
Keyword(s):  
Particulate Composite ◽  
Nanometer Range ◽  
Strain Measurements ◽  
Computer Aided

Computer-Aided Star Shot Analysis for Linac Quality Assurance Testing

2018 ◽  
Vol 205 (7) ◽  
pp. 905-911
Author(s):  
Gregory A. Szalkowski ◽  
Justin Roper
Keyword(s):  
Quality Assurance ◽  
Computer Aided

scholarly journals Computer-Aided Detection (CADe) System with Optical Coherent Tomography for Melanin Morphology Quantification in Melasma Patients

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1498
Author(s):  
I-Ling Chen ◽  
Yen-Jen Wang ◽  
Chang-Cheng Chang ◽  
Yu-Hung Wu ◽  
Chih-Wei Lu ◽  
...  
Keyword(s):  
Computer Aided Detection ◽  
Full Field ◽  
Asian Patients ◽  
Pigmentary Disorders ◽  
Area Distribution ◽  
Computer Aided ◽  
Time Observation ◽  
Cade System ◽  
Distribution Intensity ◽  
Perilesional Skin

Dark skin-type individuals have a greater tendency to have pigmentary disorders, among which melasma is especially refractory to treat and often recurs. Objective measurement of melanin amount helps evaluate the treatment response of pigmentary disorders. However, naked-eye evaluation is subjective to weariness and bias. We used a cellular resolution full-field optical coherence tomography (FF-OCT) to assess melanin features of melasma lesions and perilesional skin on the cheeks of eight Asian patients. A computer-aided detection (CADe) system is proposed to mark and quantify melanin. This system combines spatial compounding-based denoising convolutional neural networks (SC-DnCNN), and through image processing techniques, various types of melanin features, including area, distribution, intensity, and shape, can be extracted. Through evaluations of the image differences between the lesion and perilesional skin, a distribution-based feature of confetti melanin without layering, two distribution-based features of confetti melanin in stratum spinosum, and a distribution-based feature of grain melanin at the dermal–epidermal junction, statistically significant findings were achieved (p-values = 0.0402, 0.0032, 0.0312, and 0.0426, respectively). FF-OCT enables the real-time observation of melanin features, and the CADe system with SC-DnCNN was a precise and objective tool with which to interpret the area, distribution, intensity, and shape of melanin on FF-OCT images.

High-throughput screening in the diagnostics industry

2002 ◽  
Vol 30 (4) ◽  
pp. 794-797 ◽  
Author(s):  
S. Wilson ◽  
S. Howell
Keyword(s):  
Product Development ◽  
High Throughput ◽  
High Throughput Screening ◽  
Rapid Identification ◽  
Target Antigen ◽  
Cycle Times ◽  
Development Cycle ◽  
Speed Up ◽  
Product Development Cycle ◽  
Automated Screening

The diagnostics industry is constantly under pressure to bring innovation quicker to market and so the impetus to speed up product-development cycle times becomes greater. There are a number of steps in the product-development cycle where the application of high-throughput screening can help. In the case of lateral-flow immunodiagnostics the selection of antibody reagents is paramount. In particular, rapid identification of antibody pairs that are able to ‘sandwich’ around the target antigen is required. One screen that has been applied successfully is the use of surface plasmon resonance biosensors like Biacore®. Using such a system one can evaluate over 400 antibody pairings in under 5 days. Conventional approaches to screen this number of antibody pairs would take many months. Other automated screening systems like DELFIA® can be used in processing the vast amount of tests required for clinical trials. In addition, the use of robotics to automate routine product testing can be used to shorten the product-development cycle.

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