scholarly journals Development of Automatic Visual Inspection System for Fuel Cell Separator Plate

2022 ◽  
Vol 88 (1) ◽  
pp. 57-65
Author(s):  
Kimiya AOKI ◽  
Kazuki YAMAMOTO ◽  
Yusuke TAKEUCHI ◽  
Yuma HAKUMURA ◽  
Takeshi ITO ◽  
...  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lukman E. Mansuri ◽  
D.A. Patel

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.


Sensor Review ◽  
2017 ◽  
Vol 37 (4) ◽  
pp. 425-435 ◽  
Author(s):  
Annalisa Milella ◽  
Rosalia Maglietta ◽  
Massimo Caccia ◽  
Gabriele Bruzzone

Purpose Periodic inspection of large tonnage vessels is critical to assess integrity and prevent structural failures that could have catastrophic consequences for people and the environment. Currently, inspection operations are undertaken by human surveyors, often in extreme conditions. This paper aims to present an innovative system for the automatic visual inspection of ship hull surfaces, using a magnetic autonomous robotic crawler (MARC) equipped with a low-cost monocular camera. Design/methodology/approach MARC is provided with magnetic tracks that make it able to climb along the vertical walls of a vessel while acquiring close-up images of the traversed surfaces. A homography-based structure-from-motion algorithm is developed to build a mosaic image and also produce a metric representation of the inspected areas. To overcome low resolution and perspective distortion problems in far field due to the tilted and low camera position, a “near to far” strategy is implemented, which incrementally generates an overhead view of the surface, as long as it is traversed by the robot. Findings This paper demonstrates the use of an innovative robotic inspection system for automatic visual inspection of vessels. It presents and validates through experimental tests a mosaicking strategy to build a global view of the structure under inspection. The use of the mosaic image as input to an automatic corrosion detector is also demonstrated. Practical implications This paper may help to automate the inspection process, making it feasible to collect images from places otherwise difficult or impossible to reach for humans and automatically detect defects, such as corroded areas. Originality/value This paper provides a useful step towards the development of a new technology for automatic visual inspection of large tonnage ships.


1988 ◽  
Author(s):  
Hiroyuki Tsukahara ◽  
Masato Nakashima ◽  
Takefumi Inagaki

1987 ◽  
Author(s):  
Tohru Ozaki ◽  
Toshiyuki Gotoh ◽  
Takashi Toriu ◽  
Masumi Yoshida

2015 ◽  
Vol 15 (2) ◽  
pp. 269-276 ◽  
Author(s):  
Yuxiang Yang ◽  
Mingyu Gao ◽  
Ke Yin ◽  
Zhanxiong Wu ◽  
Yun Li

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