Civil and Environmental Engineering
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This is the collection for the University of Waterloo's Department of Civil and Environmental Engineering.
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Browsing Civil and Environmental Engineering by Subject "3D imaging"
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Item Construction Scene Point Cloud Acquisition, Object Finding and Clutter Removal in Real Time(University of Waterloo, 2017-08-15)Within industrial construction, piping can constitute up to 50% of the cost of a typical project. It has been shown that across the activities involved in pipe fabrication, pipe fitting has the highest impact on the critical path. The pipe fitter is responsible for interpreting the isometric drawing and then performing the tack welds on piping components so that the assembly complies with the design. Three main problems in doing this task are identified as: (1) reading and interpreting the isometric drawing is challenging and error prone for spatially complicated assemblies, (2) in assemblies with tight allowable tolerance, a number of iterations will take place to fit the pipes with compliance to the design. These iterations (rework) will remain unrecorded in the production process, and (3) no continuous measurement tool exists to let the fitter check his/her work in progress against the design information and acceptance specifications. Addressing these problems could substantially improve pipe fitters’ productivity. The objective of this research is to develop a software package integrating a threefold solution to simplify complex tasks involved in pipe fabrication: (1) making design information easier to understand, with the use of a tablet, 3D imaging device and an application software, (2) providing visual feedback on the correctness of fabrication between the design intent and the as-built state, and (3) providing frequent feedback on fabrication using a step-by-step assembly and control framework. The step-by-step framework will reduce the number of required iterations for the pipe fitter. A number of challenges were encountered in order to provide a framework to make real time, visual and frequent feedback. For frequent and visual feedback, a real time 3D data acquisition tool with an acceptable level of accuracy should be adopted. This is due to the speed of fabrication in an industrial facility. The second challenge is to find the object of interest in real time, once a point cloud is acquired, and finally, once the object is found, to optimally remove points that are considered as clutter to improve the visual feedback for the pipe fitters. To address the requirement for a reliable and real time acquisition tool, Chapter 3 explores the capabilities and limitations of low cost range cameras. A commercially available 3D imaging tool was utilized to measure its performance for real time point cloud acquisition. The device was used to inspect two pipe spools altered in size. The acquired point clouds were super-imposed on the BIM (Building Information Model) model of the pipe spools to measure the accuracy of the device. Chapter 4 adapts and examines a real time and automatic object finding algorithm to measure its performance with respect to construction challenges. Then, a K-Nearest Neighbor (KNN) algorithm was employed to classify points as being clutter or corresponding to the object of interest. Chapter 5 investigates the effect of the threshold value “K” in the K-Nearest Neighbor algorithm and optimizing its value for an improved visual feedback. As a result of the work described in this thesis, along with the work of two other master students and a co-op student, a software package was designed and developed. The software package takes advantage of the investigated real time point cloud acquisition device. While the object finding algorithm proved to be effective, a 3-point matching algorithm was used, as it was more intuitive for the users and took less time. The KNN algorithm was utilized to remove clutter points to provide more accurate visual feedback more accurate to the workers.Item Development of Transformations between Designed and Built Structural Systems and Pipe Assemblies(University of Waterloo, 2015-08-13)Fabrication of steel assemblies is a challenging process using existing machines to perform the tasks involved such as cutting, drilling, and punching. Due to inaccuracies in the fabrication processes, imperfections will inevitably happen. In addition to the fabrication inaccuracies, errors may occur during transportation or due to the temperature changes on construction sites. These challenges become more important in the offsite construction as it requires sequenced fabrication, transportation and installation. Current approaches for quality inspection, in general, and discrepancy analysis, in particular, lack a sufficient level of automation and are prone to error due to the intensive manual work involved. Hence, a proactive framework is substantially required to systematically monitor the fabrication process and control the accuracy of assemblies in order to expedite the erection and installation processes. Additionally, finding defective assemblies is traditionally done through fitting trials on construction sites, which has always been a key challenge as it is associated with rework. Furthermore, realigning the defective assemblies is currently performed based on the workers’ experience and lacks automated planning. Therefore, detecting the defective parts in a timely manner and in a systematic way can expedite the erection process and avoids significant delays in construction projects and huge costs as a consequence. This research aims to improve the fabrication and installation processes by detecting the incurred inaccuracies automatically and plan for realignment of the defective components systematically. In summary, the required framework to achieve these objectives includes four primary steps: (1) Preprocessing and basic compliance checking, (2) Spatial discrepancy detection and characterization, (3) Calculation of the required alignments and adjustments, and (4) Generalization of the realignment planning and actuation strategy frameworks for parallel systems. The automated compliance checking and discrepancy analysis is performed employing advanced 3D imaging technologies which have recently opened up a wide range of solutions to acquire as-built status. Characterization of the detected discrepancies is performed by employing robotics forward kinematics concepts and combining with 3D imaging techniques. The required alignment is calculated accordingly using the robotic analogy and inverse kinematic concept. Although the proposed approach can be applied in any types of construction assembly, this thesis mainly focuses on industrial facilities such as steel pipe modules and pipe spools, in particular. Contributions of developing the described framework include: (1) Developing a proactive strategy for rework avoidance, (2) Algorithmic and programmable framework, (3) Efficiency and robustness of the functions and metrics developed, and (4) Time effectiveness of the framework.