Jamie Yeung

State of research in automatic as-built modelling

Building Information Models (BIMs) are becoming the official standard in the construction industry for encoding, reusing, and exchanging information about structural assets. Automatically generating such representations for existing assets stirs up the interest of various industrial, academic, and governmental parties, as it is expected to have a high economic impact. The purpose of this paper is to provide a general overview of the as-built modelling process, with focus on the geometric modelling side. Relevant works from the Computer Vision, Geometry Processing, and Civil Engineering communities are presented and compared in terms of their potential to lead to automatic as-built modelling.

Quality assurance for high-frequency mechanical impact (HFMI) treatment of welds using handheld 3D laser scanning technology

The idea of using 3D point clouds obtained with the aid of a handheld 3D laser scanner for the quality assurance of high-frequency mechanical impact (HFMI) treatment is proposed and demonstrated in this paper. The effectiveness of impact treatments for extending the fatigue lives of welded structures has been demonstrated in numerous studies. Guidelines for the proper execution of impact treatments have been developed. A lack of suitable quality assurance (QA) procedures for accepting or rejecting the treatment after completion has been previously identified. In contrast with the existing QA procedures, which are based mainly on controlling inputs and visual inspection, a technology-based, quantitative methodology is developed in this paper. Five welded specimens were subjected to impact treatment at various levels to simulate under-, proper, and over-treatment. A handheld 3D laser scanner was then used to facilitate a point cloud-based method to determine the geometric parameters of the treated weld toe groove, which were then measured manually. The results show that the proposed methodology is successful in identifying the different treatment levels. This approach has a number of advantages over the existing QA methods, including the following: providing quantitative measures, ease of use, and archive-ability.

A Preliminary Investigation into Automated Identification ofStructural Steel Without A Priori Knowledge

One of the most prohibiting factors when attempting to reuse structural steel members or systems of members is the time and labour required to accurately determine dimensions. Current practices dictate that all required measurements are recorded by hand using tape measures and calipers which adds a significant cost to reused steel. To mitigate this cost, a semi-automated method for identifying structural steel components and systems is proposed that uses data acquired in the form of a 3D point cloud. Current research in the field of automated object recognition currently has two major limitations: (1) a priori knowledge, such as a building information model (BIM) is required, or (2) only simple, flat surfaces can be identified. The purpose of this study is to preliminarily investigate the possibility of automating the process of (1) cross section identification, (2) end connection geometry of bolted connections, and (3) relative component position of multi-component, planar structural systems such as trusses. Cross section identification is performed by creating filters that match standard structural sections and then convolving them over images of the cross section data. The end connection geometry is identified using Hough algorithms to detect lines and circles representing the limits of the component and the bolt holes, respectively. Planar structural systems are identified using Hough algorithms to detect lines which represent the components of the system. The results from the proposed methods show a strong potential for fully automated processes to be able to identify structural steel components and systems without a priori knowledge.

Understanding the total life cycle cost implications of reusing structural steel

Reuse of structural steel could be an environmentally superior alternative to the current practice, which is to recycle the majority (88%) of scrap steel. In spite of the potential benefits, and in a time when “sustainability” and “climate change” are critical societal issues, the question arises: why are greater rates of structural steel reuse not being observed? One of the major factors in the rate of structural steel reuse is how decision-makers understand the life cycle implications of their choice to recycle steel rather than reuse it. This paper contributes towards our understanding of these implications, particularly the cost implications, of reuse as an alternative to recycling by presenting a streamlined life cycle analysis and identifying the major contributors to each process. The results of a case study indicate that a significant reduction in some life cycle impact metrics (greenhouse gas emissions, water use) can result from reusing structural steel rather than recycling it. The largest contributors to the life cycle impact of recycling were the shredding, melting, and forming sub-processes. The largest contributor to reuse was the deconstruction sub-process. A total life cycle cost analysis is performed to understand the cost of damages to the environment and human health in combination with the cost of construction activities. Sensitivity and uncertainty analyses are also conducted to quantify variability in the results and determine economic conditions where the two processes have an equal cost.

Life cycle analysis of structural steel reuse using the economic input-output method

Reuse of structural steel is not a new concept in civil engineering. However, even though members, and assemblies of members, have been reused for decades, reuse of steel is not a widely implemented practice. Approximately 90% of demolished steel is recycled and only 10% of that steel is reused in its current state. The structural steel reuse that does occur is due to the reuse of very large members or from specialty projects. The reason for these low levels of reuse is because the cost of reusing structural steel is too high. Unfortunately, many decision makers are coming to this conclusion without a comprehensive knowledge of the true cost of reuse and recycling. In order to fully understand the additional costs, or savings, associated with steel reuse, a life cycle analysis needs to be incorporated into an economic analysis. In this study, the economic input-output method was used to perform a life cycle analysis of structural steel reuse as it compares to current practices. The economic input-output method provides the benefit of being able to facilitate a quick analysis but is limited by only being able to perform a generalized analysis across the entire industry. The analysis was performed for several metrics, which can be grouped into four categories: greenhouse gases, energy usage, water usage, and hazardous waste generation. Results from the analysis show that there is a significant decrease, upwards of 65%, for the calculated metrics across each category for reuse. In order to remedy the limitations of the economic input-output method, it is recommended to perform a similar analysis using a process model approach.

An image-based frameworks for automated discrepancy quantification and realignment of industrial assemblies

Image-based frameworks for automated as-built modeling and infrastructure 3D reconstruction are increasingly being used in the construction industry. The increasing use of image-based technologies in the construction processes is due to the ease of application, cheap cost of enhancement, time effectiveness and high level of accuracy and automation. Automating the tasks involved in the inspection, quality control and quality assurance (QA/QC) processes are the potential avenues for utilizing such frameworks. This paper presents an image-based approach for acquiring the built status of fabricated assemblies and describes a framework for realigning the defective segments by borrowing concepts from robotics and forward kinematics. A laboratory set of experiments is then conducted to measure the accuracy and performance of the proposed framework for realignment of industrial facilities, in general, and pipe spools, in particular. Results demonstrate that it can be utilized in real cases providing the required level of accuracy as well.

Robotic Kinematics Analogy for Realignment of Defective Construction Assemblies

Aligning and plumbing of construction assemblies is a fundamental problem because of reliance on manual solutions for geometric feedback control problem involved with practices such as pipefitting and steel structures erection. Where defective components and segments are not well controlled, the errors propagate in larger components and therefore cause more severe problems. In order to address such a challenging problem and tackle potential solutions, this paper presents a framework for automatic and systematic development of realignment actions required to achieve a target state by borrowing concepts from: (1) 3D imaging that enables the identification of the as-built status and then quantification of incurred discrepancies as a feedback by comparing the captured status with the designed state existing in the building information model (BIM); and (2) an inverse kinematics analogy that results in the calculation of required changes in the degrees of freedom defined where realignment and changes can be applied. Experimental results show that the framework can generate the required actions for achieving a desired state systematically and

Comparison of Methods Used for Detecting Unknown Structural Elements in Three-dimensional Point Clouds

Three-dimensional (3D) imaging technologies, in particular 3D laser scanners, are becoming more accessible and more accurate. These advances are providing engineers and architects with vast quantities of raw, geometric data. Whereas this data is visually appealing and intuitive to the human eye, it contains very little meaning beyond that. The research presented in this paper presents and compares methods for attributing meaning to dense 3D point clouds. Two of the methods developed and presented utilize two-dimensional (2D) and 3D Hough transforms to represent the points as lines and planes. The third method uses point segmentation techniques to group points belonging to the same plane. The initial focus is on structural steel systems and connections modeling for analysis of reuse. The advantages and disadvantages of each method are outlined, and each method is evaluated for its potential to provide engineers and architects with useful and meaningful point clouds from 3D laser scanners. The point segmentation techniques exhibit the most potential by allowing for the location and orientation of any surface to be identified.

Automated Deviation Analysis for As-Built Status Assessment of Steel Assemblies and Pipe Spools

Steel assemblies and pipe spools play an essential role in the industrial construction sector. Fabrication of steel assemblies has been a challenging task due to the limited fabrication precision of the tools used in the process and inadequate inspection during fabrication. Moreover, unfavorable deformations may occur during the transportation phase which makes the erection and installation phase more complicated. These deviations require further considerations for realignment and repair that are associated with rework on construction sites. Hence, a systematic and automatic framework is required to continuously monitor the fabrication and installation processes of steel assemblies. Current approaches lack a sufficient level of control and are prone to error. This paper presents an automated framework to detect defective parts in steel assemblies and pipe spools in particular. A laser-based point cloud, which represents the as-built status, is compared to the original state from the CAD drawings that exist in the Building Information Model (BIM). Therefore, the defective parts are detected in a timely manner. The comparison is distance based and the procedure is fully automated. The experiments conducted to validate the proposed approach show that the model has high precision and a high rate of recall and has the potential to be employed for automated damage detection in order to improve productivity on construction sites. PROBLEM STATEMENT Steel structural assemblies are one of the critical components in both residential and industrial construction. Pipe spools are also key components for most industrial construction projects such as refineries and power plants. Utilizing steel structural assemblies on construction sites requires accurate fabrication and incident free shipment to site. Due to the advantages that staged fabrication of modules provides such as a controlled environment for fabrication, improved safety and improved