scholarly journals An Automatic Road Distress Visual Inspection System Using an Onboard In-Car Camera

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Thitirat Siriborvornratanakul
Keyword(s):  
Preventive Maintenance ◽  
Visual Inspection ◽  
Current System ◽  
Ease Of Use ◽  
Capital City ◽  
Inspection System ◽  
Maintenance Strategy ◽  
Road Maintenance ◽  
Proof Of Concept ◽  
Road Inspection

Speaking of road maintenance, the preventive maintenance strategy is preferable for most governments. Many governments possess special vehicles that can accurately detect and classify many types of road distresses. By running these vehicles frequently, small road distresses will be detected before growing into the big ones. However, because running these huge and expensive vehicles is not easy, in practical, it usually ends up with infrequent road inspection regardless of having automatic road inspection vehicles. In this paper, we focus on investigating and developing an automatic and nondestructive visual inspection system whose setup and usage are designed by considering the context of drivers, driving styles, and road conditions in Bangkok, the capital city of Thailand. Our proposal includes a workflow diagram of a vision-based road inspection system that is capable of detecting, classifying, tracking, measuring, and pricing road distresses. As for the proof-of-concept, our current system focuses on detecting one specific type of road distresses called pothole, using only one onboard in-car camera. Experimental results reveal that the context of Bangkok introduces many nontrivial challenges for vision-based analysis systems where maintaining both accuracy and ease of use altogether may not be easy.

scholarly journals INTELLIGENT MACHINE VISION BASED RAILWAY INFRASTRUCTURE INSPECTION AND MONITORING USING UAV

2019 ◽  
Vol 17 (3) ◽  
pp. 357 ◽  
Author(s):  
Milan Banić ◽  
Aleksandar Miltenović ◽  
Milan Pavlović ◽  
Ivan Ćirić
Keyword(s):  
Machine Vision ◽  
Visual Inspection ◽  
Cost Effective ◽  
Extraction Methods ◽  
Ease Of Use ◽  
Inspection System ◽  
Infrastructure Monitoring ◽  
Vision Sensors ◽  
Railway Infrastructure ◽  
Infrastructure Inspection

Traditionally, railway inspection and monitoring are considered a crucial aspect of the system and are done by human inspectors. Rapid progress of the machine vision-based systems enables automated and autonomous rail track detection and railway infrastructure monitoring and inspection with flexibility and ease of use. In recent years, several prototypes of vision based inspection system have been proposed, where most have various vision sensors mounted on locomotives or wagons. This paper explores the usage of the UAVs (drones) in railways and computer vision based monitoring of railway infrastructure. Employing drones for such monitoring systems enables more robust and reliable visual inspection while providing a cost effective and accurate means for monitoring of the tracks. By means of a camera placed on a drone the images of the rail tracks and the railway infrastructure are taken. On these images, the edge and feature extraction methods are applied to determine the rails. The preliminary obtained results are promising.

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 Road maintenance strategy with characteristic of drainage condition based on pavement performance

2018 ◽  
Author(s):  
Dadang Iskandar ◽  
Sigit Pranowo Hadiwardoyo ◽  
Raden Jachrizal Sumabrata ◽  
Ika Nur Fitriasari
Keyword(s):  
Pavement Performance ◽  
Maintenance Strategy ◽  
Road Maintenance

Preventive maintenance optimization for repairable products considering two-dimensional warranty and customer satisfaction

2018 ◽  
Vol 233 (4) ◽  
pp. 553-566
Author(s):  
Yukun Wang ◽  
Yiliu Liu ◽  
Aibo Zhang
Keyword(s):  
Customer Satisfaction ◽  
Preventive Maintenance ◽  
Product Performance ◽  
Maintenance Optimization ◽  
Two Dimensional ◽  
Maintenance Strategy ◽  
Minimal Repair ◽  
Proposed Model ◽  
Useful Life ◽  
Practical Implications

Customer satisfaction with a purchased product is closely related to the product performance within the warranty region and even the performance during the remainder of its useful life. Every satisfied customer may boost the future sales of the same product with positive evaluations and recommendations to others, and thus will create more profits for the manufacturer. During the useful life of the product, the expected cost to the manufacturer normally depends on the warranty policy, product reliability and specific servicing strategies implemented. In this article, considering the effect of customer satisfaction on the manufacturer’s incurred cost, we investigate a periodic and imperfect preventive maintenance strategy for repairable products sold with a two-dimensional warranty policy. The customer satisfaction is measured with the probability of the customer making a repeat purchase from the same manufacturer. In the proposed model, the number of preventive maintenance actions and corresponding maintenance level are jointly derived with the objective of minimizing the expected total cost per product to the manufacturer. The performance of the proposed preventive maintenance strategy is compared with that of minimal repair corrective maintenance strategy in a numerical example, so as to illustrate its applicability. In addition, some practical implications from a detailed sensitivity analysis are elaborated.

scholarly journals INVESTIGATION INTO TRAFFIC FLOWS ON HIGH INTENSITY STREETS OF VILNIUS CITY

Transport ◽  
2010 ◽  
Vol 25 (3) ◽  
pp. 244-251 ◽  
Author(s):  
Laura Žiliūtė ◽  
Alfredas Laurinavičius ◽  
Audrius Vaitkus
Keyword(s):  
Traffic Safety ◽  
Traffic Volume ◽  
Capital City ◽  
State Enterprise ◽  
Traffic Intensity ◽  
Road Maintenance ◽  
Traffic Flows ◽  
The Road ◽  
Maintenance Program ◽  
Road Research Laboratory

The measurements and analysis of traffic intensity were performed in the capital city – Vilnius, the largest urban area in Lithuania. Vilnius is a centre of business, industry and tourism, and therefore traffic intensity remains the highest in this part of the country. The intensity of vehicle traffic is not only generally calculated but also simultaneously classified which means is divided predefining vehicles into beforehand established categories. Data on traffic flows are used in a road maintenance program for calculating and assessing air pollution, ensuring traffic safety, regulating traffic flows etc. The article presents the methods for measuring traffic intensity which are and were used for calculating traffic intensity not only in the streets of Vilnius but also across Lithuania. Data on vehicle intensity and classification are collected either using technologies (loop and tube detectors, counters and video detectors) or expressing them visually. The article presents the dynamics of changes in the traffic volume on the roads of Lithuania for the period 2000–2009. Also, this article examines traffic intensity of all transport means, including trucks in the permanent traffic volume measuring stations that were installed near the roads in Vilnius zone (data on traffic for the period 2005–2009) and the streets of Vilnius city (data on traffic for the period 2007–2009). Data on traffic intensity were obtained by the Road Research Laboratory of the Road Department of Vilnius Gediminas Technical University in cooperation with the State Enterprise Transport and Road Research Institute (TRRI).

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