An approach for real world data modelling with the 3D terrestrial laser scanner for built environment

Capturing and modelling 3D information of the built environment is a big challenge. A number of techniques and technologies are now in use. These include EDM, GPS, and photogrammetric application, remote sensing and traditional building surveying applications. However, use of these technologies cannot be practical and efficient in regard to time, cost and accuracy. Furthermore, a multi disciplinary knowledge base, created from the studies and research about the regeneration aspects is fundamental: historical, architectural, archeologically, environmental, social, economic, etc. In order to have an adequate diagnosis of regeneration, it is necessary to describe buildings and surroundings by means of documentation and plans. However, at this point in time the foregoing is considerably far removed from the real situation, since more often than not it is extremely difficult to obtain full documentation and cartography, of an acceptable quality, since the material, constructive pathologies and systems are often insufficient or deficient (flat that simply reflects levels, isolated photographs,..). Sometimes the information in reality exists, but this fact is not known, or it is not easily accessible, leading to the unnecessary duplication of efforts and resources. In this paper, we discussed 3D laser scanning technology, which can acquire high density point data in an accurate, fast way. Besides, the scanner can digitize all the 3D information concerned with a real world object such as buildings, trees and terrain down to millimetre detail Therefore, it can provide benefits for refurbishment process in regeneration in the Built Environment and it can be the potential solution to overcome the challenges above. The paper introduce an approach for scanning buildings, processing the point cloud raw data, and a modelling approach for CAD extraction and building objects classification by a pattern matching approach in IFC (Industry Foundation Classes) format. The approach presented in this paper from an undertaken research can lead to parametric design and Building Information Modelling (BIM) for existing structures. Two case studies are introduced to demonstrate the use of laser scanner technology in the Built Environment. These case studies are the Jactin House Building in East Manchester and the Peel building in the campus of University Salford. Through these case studies, while use of laser scanners are explained, the integration of it with various technologies and systems are also explored for professionals in Built Environmen

Integrated Reverse Modeling Techniques for the Survey of Complex Shapes in Industrial Design

This chapter proposal deals with three-dimensional survey methods applied to the geometrical acquisition of Industrial Design products. 3D acquisition techniques are defined by well-know procedures that nowadays are applied in a lot of fields, from Mechanics to Aerospace, from Robotics to Cultural Heritage. In the last years the impressive technology evolution used for developing hardware and software allowed to reach excellence peaks in the 3D instruments application. At the same time a lot of experiments and researches were leaded in order to reach a well structured pipeline of reverse modeling process, supporting the process from the real object to its digital mould. In the last decade 3D acquisition and modeling techniques tried to support Industrial Design production, but their role in every single process is not yet systematically codified for some bottlenecks present in the design process and in product knowledge, that will be discussed in the chapter in relation with the state of the art of the current technology. In addition the level of geometrical complexity of any specific product often highlight limitations in the use of a single 3D laser scanner technology, which can’t reach good results with all the typologies of Industrial Design products. These factors are critically framed, outlining the definition of object complexity towards the suited choice of survey methods and technologies for every condition. The actual limits of 3D acquisition systems will be identified and compared to integrate ones (i.e. systems composed by different complementary instruments are used together) applied in different fields, from Car Design to Product Restyling, from Nautical Analysis to Design in Cultural Heritage. The aim of the contribution is to demonstrate the intrinsic limits of a single 3D instrument application and the necessity to apply multi-resolution system or sensor fusion to solve the larger part of the problems in the 3D acquisition of complex shapes

Terrestrial Laser Scanning-Based Bridge Structural Condition Assessment

Objective, accurate, and fast assessment of a bridge’s structural condition is critical to the timely assessment of safety risks. Current practices for bridge condition assessment rely on visual observations and manual interpretation of reports and sketches prepared by inspectors in the field. Visual observation, manual reporting, and interpretation have several drawbacks, such as being labor intensive, subject to personal judgment and experience, and prone to error. Terrestrial laser scanners (TLS) are promising sensors for automatically identifying structural condition indicators, such as cracks, displacements, and deflected shapes, because they are able to provide high coverage and accuracy at long ranges. However, limited research has been conducted on employing laser scanners to detect cracks for bridge condition assessment, and the research has mainly focused on manual detection and measurement of cracks, displacements, or shape deflections from the laser scan point clouds. This research project proposed to measure the performance of TLS for the automatic detection of cracks for bridge structural condition assessment. Laser scanning is an advanced imaging technology that is used to rapidly measure the three-dimensional (3D) coordinates of densely scanned points within a scene. The data gathered by a laser scanner are provided in the form of point clouds, with color and intensity data often associated with each point within the cloud. Point cloud data can be analyzed using computer vision algorithms to detect cracks for the condition assessment of reinforced concrete structures. In this research project, adaptive wavelet neural network (WNN) algorithms for detecting cracks from laser scan point clouds were developed based on the state-of-the-art condition assessment codes and standards. Using the proposed method for crack detection would enable automatic and remote assessment of a bridge’s condition. This would, in turn, result in reducing the costs associated with infrastructure management and improving the overall quality of our infrastructure by enhancing maintenance operations

Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification

Product optimization for casting and post-casting manufacturing processes is becoming compulsory to compete in the current global manufacturing scenario. Casting design, simulation and verification tools are becoming crucial for eliminating oversized dimensions without affecting the casting component functionality. Thus, material and production costs decrease to maintain the foundry process profitable on the large-scale component supplier market. New measurement methods, such as dense matching techniques, rely on surface texture of casting parts to enable the 3D dense reconstruction of surface points without the need of an active light source as usually applied with 3D scanning optical sensors. This paper presents the accuracy evaluation of dense matching based approaches for casting part verification. It compares the accuracy obtained by dense matching technique with already certified and validated optical measuring methods. This uncertainty evaluation exercise considers both artificial targets and key natural points to quantify the possibilities and scope of each approximation. Obtained results, for both lab and workshop conditions, show that this image data processing procedure is fit for purpose to fulfill the required measurement tolerances for casting part manufacturing processes.This research was partially funded by ESTRATEUS project (Reference IE14-396). given are accurate and use the standard spelling of funding agency names at https://search.crossref.org/funding, any errors may affect your future funding

Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)

Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft

3d Scanning And The Impact Of The Digital Thread On Manufacturing And Re-Manufacturing Applications

3D laser line scanners are becoming a powerful technology for capturing point cloud datasets and collecting dimensional information for many objects. However, the use of point cloud is limited due to many factors. These include the lack of on deep understanding of the effect of point cloud parameters on scan quality. This knowledge is critical to gaining an understanding of the measurement in point cloud. Currently, there are no adequate measurement procedures for 3D scanners. There is a need for standardized measurement procedures to evaluate 3D scanner accuracy due to uncertainties in 3D scanning, such as surface quality, surface orientation and scan depth [6]. The lack of standardized procedures does not allow the technology to be fully automated and used in manufacturing facilities that would allow 100% in-line inspection. In this dissertation I worked on accomplishing four tasks that will achieve the objective of having a standardized measurement procedure that is critical to develop an automated laser scanning system to avoid variations and have consistent data capable of identifying defects. The four tasks are: (1) linking the robot workspace with the scanner workspace; (2) studying the effect of the scanning speed and the resolution on point cloud quality by conducting an experiment with systematically varied scan parameters on scan quality; (3) studying the overall error of that is associated with the transformation of the point cloud in a remanufacturing facility using additive manufacturing. The parameters that were tested are the effect of view angle, standoff distance, speed, and resolution. Knowing the effect of these parameters is important in order to generate the scan path that provides the best coverage and quality of points collected. There is also a need to know the impact of all the scanning parameters especially the speed and the resolution; (4) modeling a machine learning tool to optimize the parameters of different scanning techniques after collecting the scanning results to select the optimal ones that provide the best scan quality. With the success of this work, the advancement and practice of automated quality monitoring in manufacturing will increase