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Amin Hammad, Yongxin Hu

Location-Based Bridge Inspection Decision-Support System

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Series: w78:2006 (browse)
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Blanca Quintana, Samuel A. Prieto, Antonio Adan and Frédéric Bosché

Scan-To-BIM for Small Building Components

Abstract: Scan-to-BIM works have so far mainly focused on 'structural' components such as floors, ceiling, walls (with doors and windows). But, the control of new facilities and the production of their corresponding as-is BIM models requires the identification and inspection of numerous other building components and objects, e.g. MEP components such as plugs, switches, ducts, and signs. In this paper, we present a novel 6D-based (XYZ + RGB) approach that processes dense coloured 3D points provided by terrestrial laser scanners to recognize such smaller objects that are commonly located on walls. This paper focuses on the recognition of objects such as sockets, switches, signs, and extinguishers. After segmenting the point clouds corresponding to the walls of a building, a set of candidate objects are detected independently in the colour and geometric spaces, and a consensus procedure integrates both results to infer recognition. The method has been tested on real indoors yielding promising results.

Keywords: Object Recognition, Scan-To-BIM, Automatic BIM, 3D Data Processing

DOI: https://doi.org/10.24928/JC3-2017/0139

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Byeongju Lee, Wontae Lee, Changkeun Lee

Development Of A Remote Control System For Bridge Inspection Using Robot And Digital Image Processing Technology

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C Klinzmann & D Hosser

Probabilistic Building Inspection and Life Assessment - a computer program for reliability based system assessment

Abstract: The collaborative research centre (CRC) 477 explores innovative methods for structural health monitoring. In project field A1, methods and strategies, the modular knowledge-based computer program PROBILAS (Probabilistic Building Inspection and Life ASsessment) is developed. Its main focus lies on the optimization of structural health monitoring measures. One opportunity to optimize the monitoring process is to concentrate the monitoring measures on a few critical weak points of a structure. These critical weak points are identified by using methods of the system and reliability theory. Additionally these methods provide the opportunity to evaluate and to assess the probability of failure of a system. This paper concentrates on the implementation of the described methods into PROBILAS. Especially the database model, its integration into the program modules and the calculation procedure used for reliability analysis are discussed further.

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Full text: content.pdf (329,245 bytes) (available to registered users only)

Series: w78:2005 (browse)
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Permission to reproduce these papers has been graciously provided by the Technische Universität Dresden.


Chang L M, Chen P H, Abdelraziq Y

Bridge painting defects recognition using samplying plans and image processing techniques

Abstract: Bridge painting inspection is a time-consuming work that relies on plenty of human visual efforts that are subjective, inefficient, and inaccurate. In order to shorten the inspection / evaluation time and increase the accuracy, two unbiased sampling plans and an automated recognition system were developed with the hope of standardizing and automating the inspection process. The system hybridizes image processing techniques and neural networks, which provide expert knowledge through training, to automatically diagnose the defects on an image. The developed recognition system can process vast number of images instantly and intelligently with simulated human expertise. The detection of rust areas is used to exemplify the recognition system.

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Full text: content.pdf (382,147 bytes) (available to registered users only)

Series: w78:2000 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.analysis (0.041745) class.synthesis (0.010450) class.strategies (0.006286)
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Permission to reproduce these documents have been graciously provided by Icelandic Building Research Institute. The assistance of the editor, Mr. Gudni Gudnason, is gratefully appreciated


Chang L-M, Abdelrazig Y A

Using images pattern recognition and neural networks for coating quality assessment

Abstract: Most current techniques used in construction and infrastructure assessment and quality inspection rely merely on subjective criteria. Such inaccurate or subjective assessment techniques have been identified as a critical obstacle to effective infrastructure or constructed facilities management. This paper illustrates a more objective and reliable assessment method to improve the conditions of the infrastructures or the quality of constructed facilities. The proposed system will automate the coating assessment process by using computers to analyze digital images of the areas to be assessed.

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Full text: content.pdf (173,112 bytes) (available to registered users only)

Series: w78:1999 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.analysis (0.038911)
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Permission to reproduce these papers has been graciously provided by the Research Press of the National Research Council of Canada. The support of the editors, particularly Dr. Dana Vanier, is gratefully appreciated.


Chou S-A, Chen C-C, Wang J, Chen K-C, Chen L-M

A knowledge-based system for dam safety assessment in taiwan

Abstract: In Taiwan, the assessment of dam safety is normally carried out by either visual inspection orstatistical analysis of monitoring data. The process is time-consuming and to a great extent relies onthe knowledge and expertise of the personnel. With increasing power in computing facilities,systematic approaches that adopt knowledge-based expert system techniques are potential solutionsfor managing dam safety in Taiwan. In this study, we investigate recent advances in this field andpropose a knowledge-based expert system for conducting dam safety assessment in Taiwan. Theframework and the weighting system of this system are discussed.

Keywords: dam safety assessment, knowledge-based system, web applications

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Series: ecce:2001 (browse)
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Cox S, Perdomo J, Thabet W

Construction field data inspection using pocket PC technology

Abstract: Construction projects are characterized by the large amount of data that needs to be collected, processed, and exchanged among the different project participants. Collection of construction inspection data, in particular, allows field personnel to monitor project performance with the ultimate goal of improving productivity and lowering costs. Current practices for recording and filing of field inspection data are mainly paper-based. This manual process using paper forms is a time consuming and tedious task. Not only is the clerical expense of this process very high, but also the organization and review of the information commands an inordinate amount of time by a project manager, of which most managers posses very little. Continuous evolvement and improvements of the Pocket PC and its hardware/software technologies, including more powerful processors, smaller storage devices, higher quality displays, and wide availability of third party application software, have made it possible for these devices to become stand alone systems with powerful functional capabilities. Because of their high mobility characteristics due to their small size and light weight, Pocket PCs can be used in the construction field to perform various tasks including recording of inspection data. This paper describes an application for automating the collection process of field inspection data using Pocket PCs. The application allows for recording, processing, and distribution of quality compliance inspection information of various tasks performed in the field. The application is developed using HandBaseTM database software from DDH Software, Inc. and is implemented using a Compaq iPAQ H3870 Pocket PC.

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Full text: content.pdf (451,415 bytes) (available to registered users only)

Series: w78:2002 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.man-man (0.013437) class.software-software (0.008948) class.store (0.005362)
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Permission to reproduce these documents have been graciously provided by the Aarhus School of Architecture, Denmark. The assistnace of the editor, Prof. Kristian Agger, is gratefully aprecciated.


Damien Serre, Pierre Maurel, Laurent Peyras and Youssef Diab

A Spatial Decision Support System To Optimize Inspection, Maintenance And Reparation Operations Of River Levees

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Full text: content.pdf (1,385,810 bytes) (available to registered users only)

Series: w78:2006 (browse)
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Danijel Rebolj, Riko Šafarič, Andrej Šorgo and Nenad Čuš Babič

SMARTCON, Self-Maintaining and Rejuvenating Constructions

Abstract: Infrastructure systems are established and maintained to satisfy our societal needs for living and transport. The European Roadmap for Cross-Modal Transport Infrastructure Innovation states that by 2030 an improvement of 50% in infrastructure performance, risk and cost versus a 2010 baseline should be achieved. However, current maintenance methods require intense engagement of highly trained experts and exposure to hazards, they are time consuming and hinder the normal use of constructions. Since infrastructure systems are not able to "care for themselves" they create a heavy burden for society in terms of regular maintenance and total cost of ownership. Therefore, SMARTCON proposes to transform passive constructions into smart structures able to take care of themselves. The envisaged system shall consist of a biomimetic swarm of robots able to perform continuous inspection, analysis of inspected indicators, decision support systems to advise on necessary maintenance or rejuvenation actions and to evaluate implemented actions. The paper is presenting the SMARTCON concept, the preliminary research, and the intended results of a three-year project beginning in early 2017. The project is focusing on bridges as they are considered to be among the most critical infrastructure objects.

Keywords: Automation, Infrastructure, Bridges, Inspection, Maintenance, Rejuvenation, Robot Swarm, Biomimetics

DOI: https://doi.org/10.24928/JC3-2017/0164

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Series: jc3:2017 (browse)
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