Design and Implementation of Visual Inspection System in Automatic Bottling System Based on PLC

2008 ◽  
Author(s):  
Denni Kurniawan ◽  
Riza Sulaiman
Keyword(s):  
Visual Inspection ◽  
Inspection System ◽  
Design And Implementation

scholarly journals A novel visual inspection system for rail surface spalling detection

2021 ◽  
Vol 1048 (1) ◽  
pp. 012015
Author(s):  
Dieuthuy Pham ◽  
Minhtuan Ha ◽  
Changyan Xiao
Keyword(s):  
Visual Inspection ◽  
Inspection System

Visual inspection system using multidirectional 3-D imager

1991 ◽  
Author(s):  
Tetsuo Koezuka ◽  
Yoshikazu Kakinoki ◽  
Shinji Hashinami ◽  
Masato Nakashima
Keyword(s):  
Visual Inspection ◽  
Inspection System

Artificial intelligence-based automatic visual inspection system for built heritage

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lukman E. Mansuri ◽  
D.A. Patel
Keyword(s):  
Artificial Intelligence ◽  
Visual Inspection ◽  
Image Data ◽  
Inspection System ◽  
Data Set ◽  
Web Based ◽  
Content Type ◽  
Built Heritage ◽  
Automatic Visual Inspection ◽  
Inspection Systems

PurposeHeritage is the latent part of a sustainable built environment. Conservation and preservation of heritage is one of the United Nations' (UN) sustainable development goals. Many social and natural factors seriously threaten heritage structures by deteriorating and damaging the original. Therefore, regular visual inspection of heritage structures is necessary for their conservation and preservation. Conventional inspection practice relies on manual inspection, which takes more time and human resources. The inspection system seeks an innovative approach that should be cheaper, faster, safer and less prone to human error than manual inspection. Therefore, this study aims to develop an automatic system of visual inspection for the built heritage.Design/methodology/approachThe artificial intelligence-based automatic defect detection system is developed using the faster R-CNN (faster region-based convolutional neural network) model of object detection to build an automatic visual inspection system. From the English and Dutch cemeteries of Surat (India), images of heritage structures were captured by digital camera to prepare the image data set. This image data set was used for training, validation and testing to develop the automatic defect detection model. While validating this model, its optimum detection accuracy is recorded as 91.58% to detect three types of defects: “spalling,” “exposed bricks” and “cracks.”FindingsThis study develops the model of automatic web-based visual inspection systems for the heritage structures using the faster R-CNN. Then it demonstrates detection of defects of spalling, exposed bricks and cracks existing in the heritage structures. Comparison of conventional (manual) and developed automatic inspection systems reveals that the developed automatic system requires less time and staff. Therefore, the routine inspection can be faster, cheaper, safer and more accurate than the conventional inspection method.Practical implicationsThe study presented here can improve inspecting the built heritages by reducing inspection time and cost, eliminating chances of human errors and accidents and having accurate and consistent information. This study attempts to ensure the sustainability of the built heritage.Originality/valueFor ensuring the sustainability of built heritage, this study presents the artificial intelligence-based methodology for the development of an automatic visual inspection system. The automatic web-based visual inspection system for the built heritage has not been reported in previous studies so far.

scholarly journals Visual Inspection System for Insulators in Power Plant.

1993 ◽  
Vol 11 (7) ◽  
pp. 1093-1104
Author(s):  
Miwako HIROOKA ◽  
Yasushi YAGI ◽  
Shinjiro KAWATO
Keyword(s):  
Power Plant ◽  
Visual Inspection ◽  
Inspection System

Progress toward an automated visual inspection system

1990 ◽  
Author(s):  
P. COLEMAN ◽  
S. NELSON ◽  
J. MARAM ◽  
A. NORMAN
Keyword(s):  
Visual Inspection ◽  
Inspection System ◽  
Automated Visual Inspection
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