Hoon Sohn

Active dimensional quality assessment of precast concrete using 3D laser scanning

Quality assessment of precast concrete panels is an important factor that affects overall quality of construction. As prefabrication becomes popular at construction sites, demands for automatic and accurate inspections of the dimensions of the precast concrete panels have increased. Current techniques for measuring the dimensions of precast concrete panels, however, heavily rely on qualified inspectors, and are time and labor demanding. To overcome these limitations, a dimensional measurement technique for precast concrete panels is proposed using a 3D laser scanner. For autonomous implementation of the dimensional measurement, a new feature extraction algorithm of extracting only boundary points of the precast concrete panels is developed. To increase the measurement accuracy, a compensation model is employed to account for the dimension losses caused by an intrinsic limitation of laser scanners. This study focuses on measurements of length, width and squareness of precast concrete panels in a noncontact and speedy manner. Experimental validations on actual precast slabs are conducted to verify the applicability of the proposed dimensional measurement technique for precast concrete panels.

Formulation of a framework for quality assessment of precast concrete based on 3D laser scanning

This study presents a framework for quality inspect ion of precast concrete components using the 3D laser scanning technique. As precast concrete-ba s d rapid bridge construction is getting standardiz ed, quality assessment of the precast concrete becomes critical for preventing any failures during the construction process. Moreover, as Building Informa tion Modeling (BIM) gains popularity in the construction industry, autonomous and intelligent i nspection systems are needed. Current method for quality control of precast concrete components, how ever, heavily relies on visual inspection and conta cttype measurements, which are time and labor demandi ng. Also, storage and delivery systems of inspectio n information such as the procedures and results of q uality inspection are lacking. To overcome these limitations of the current quality assessment techn ique for precast concrete, this study aims to devel op a BIM-based framework for efficient quality inspectio n of precast concrete with the use of a 3D laser scanner. First, we formulate practical guidelines i ncluding detailed inspection procedure, selection o f optimized scanner and scan location, inspection cri teria, and data storage and delivery system. Second , t investigate the applicability of 3D laser scanning to precast concrete quality inspection based on the proposed framework, a case study inspecting quality of a lab-scale object assumed as precast concrete component is presented for detecting defects.

Full-Scale Application of a Dimensional Quality Assessment Technique to Precast Concrete Panels using Terrestrial Laser Scanning

Nowadays, precast concrete panels are one of the most popular construction components. To safeguard the overall quality of construction projects, it is important to ensure that the dimensional quality of precast concretes conform to the design specifications. In order to achieve this, a terrestrial laser scanning (TLS)-based automated dimensional quality assessment technique has been developed by the author’s group. The scope of this paper is such that the developed dimensional quality assessment technique is further advanced so that this technique can also be applied to full-scale precast concrete panels with complex geometries. A full-scale precast slab with dimensions of 10,610 mmx1,980 mm in a precast manufacturing company is used as a test target to validate the effectiveness of the dimensional quality assessment technique. The challenges encountered during the data analysis of the full-scale test are investigated and resolved using optimized algorithms. Furthermore, comparison of the effectiveness between the conventional technique (deviation analysis) and the proposed technique is conducted. The average dimensional error for the proposed technique is 5.2 mm, while that of the conventional deviation analysis is 10.2 mm, demonstrating that the proposed technique can have high potentials in estimating and assessing the dimensional properties of the precast concrete panel.

Automated Quality Inspection of Precast Concrete Elements with Irregular Shapes Using Terrestrial Laser Scanner and BIM Technology

Nowadays precast concrete elements are widely used in buildings, bridges, and other civil infrastructure facilities because precast elements allow rapid construction and high precision quality control. However, the quality inspection of precast concrete elements primarily relies on manual inspection, which is time consuming and error-prone. Recently, terrestrial laser scanner (TLS) has been used to improve quality inspection. The authors’ group has previously developed an automated dimension estimation technique for precast concrete elements, but its applicability is limited only to precast elements with rectangular shapes. This study advances our previous work so that the dimensions of precast elements with irregular shapes can also be automatically estimated. First, a density-based clustering algorithm is adopted to extract target objects from 3D point cloud data acquired by a TLS. Then, coarse registration is conducted to match each object extracted from the 3D point cloud with the asdesign objects in building information models (BIM) one by one. Thirdly, all point cloud data points are registered onto different surfaces of the as-designed objects in BIM through fine registration. Lastly, the as-built dimensions of the precast concrete element are extracted and compared with the as-design ones in BIM. The effectiveness and accuracy of the developed technique are examined using point cloud data obtained from a laboratory-scale precast concrete bridge deck panel.