Requirements for Measuring Inspection System Performance

2021 ◽  
pp. 346-353
Author(s):  
Colin G. Drury ◽  
Catherine Drury Barnes
Keyword(s):  
System Performance ◽  
Inspection System

AFP Automated Inspection System Performance and Expectations

2017 ◽  
Author(s):  
Joshua Cemenska ◽  
Todd Rudberg ◽  
Michael Henscheid ◽  
Andrew Lauletta ◽  
Bradley Davis
Keyword(s):  
System Performance ◽  
Inspection System ◽  
Automated Inspection

Impact of task complexity on hybrid inspection system performance

2003 ◽  
Author(s):  
Xiaochun Jiang ◽  
Mohammad T. Khasawneh ◽  
Sittichai Kaewkuekool ◽  
Shannon R. Bowling ◽  
William Taylor ◽  
...  
Keyword(s):  
System Performance ◽  
Task Complexity ◽  
Inspection System

3D monitoring of woody crops using an unmanned ground vehicle

2017 ◽  
Vol 8 (2) ◽  
pp. 210-215 ◽  
Author(s):  
A. Ribeiro ◽  
J. M. Bengochea-Guevara ◽  
J. Conesa-Muñoz ◽  
N. Nuñez ◽  
K. Cantuña ◽  
...  
Keyword(s):  
System Performance ◽  
High Performance ◽  
Inspection System ◽  
Unmanned Ground Vehicle ◽  
Complementary Information ◽  
Heterogeneous Information ◽  
Ground Vehicle ◽  
Woody Crops ◽  
Custom Software ◽  
High Performance Computer

This paper presents an inspection system integrated into an on-ground autonomous platform with range of approximately 80 km. The vehicle is prepared to autonomously cover a field following a predefined route plan. Two types of cameras were integrated in the platform. An RGB-D sensor and a reflex camera were placed in a fixture and connected to a high-performance computer. The heterogeneous information acquired from the RGB-D was later integrated to automatically generate 3D maps of the crops by using custom software developed in the authors’ previous work. The inspection system performance was tested in actual vineyards by conducting several samplings in 2016. Results show that the proposed technology is viable and can provide complementary information to other inspection alternatives.

scholarly journals Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning

2021 ◽  
Vol 17 (2) ◽  
pp. 1-7
Author(s):  
Ahmed Najah ◽  
Faiz F. Mustafa ◽  
Wisam S. Hacham
Keyword(s):  
Neural Networks ◽  
Environmental Factors ◽  
Transfer Learning ◽  
System Performance ◽  
Inspection System ◽  
Learning Approach ◽  
Quality Inspection ◽  
Helical Gears ◽  
High Resolution Images ◽  
Low Costs

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poor settings of lighting, background, distance and camera resolution. Experimental results implied that the system was able to show high accuracies above 90% at very bad settings and around 99% at good settings, which assures that an inspection system with good performance can be built at low costs.  

Impact of Task Complexity on Hybrid Inspection System Performance

2003 ◽  
Vol 47 (18) ◽  
pp. 1958-1961
Author(s):  
Xiaochun Jiang ◽  
Mohammad T. Khasawneh ◽  
Sittichai Kaewkuekool ◽  
Shannon R. Bowling ◽  
William Taylor ◽  
...  
Keyword(s):  
System Performance ◽  
Task Complexity ◽  
Inspection System
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