Automated Quality Assessment of Precast Members using Lidar and Augmented Reality

Prefabrication practices have been developed to manufacture concrete components of infrastructures in factories, transporting them to construction sites, and ultimately assembling them as final products onsite. However, there are a few problems with these processes, such as inaccuracy in benefit evaluation methods, and difficulties in the quality management of prefabricated construction projects. If we could track the quality in the fabrication process, then it is easier to keep a permanent record from cradle to grave for future implementations. Construction, fabrication, and final product tolerances describe the dimensional relationships of each precast component that make up a whole structure at the different stages of production which will ultimately affect their durability and service life. It is crucial that the form’s dimensions are correct so that the manufactured product has the correct tolerances. Also, it is important to have a clear understanding of the appropriate product tolerances before a project begins, along with the correct interfacing tolerances and erection tolerances. This creates clear expectations for the project and ensures that everyone is working within the same agreed tolerances. This research project will develop an augmented reality (AR) tool and interface as well as scanning in the field that enables easy information access, automatic data collection, and real-time data analysis by providing a dimensional verification of precast members inspection using 3D scanning. The focus will be prestressed I-beams that are cast in New Mexico, but it can be used for box girders, and other beams of interest in other transportation infrastructure. This research aims to develop an innovative framework utilizing 3D point cloud data to provide insights into production variations. The objective is to empower factory operators with actionable information for enhancing quality control and optimizing processes with an interface both with the data and the product itself so it can be rectified in the field. To facilitate efficient decision-making by inspectors, a solution will be developed to expedite the identification of incorrect precast strands, rebar, stirrups, chairs, spacers, plates, and eventually the concrete dimensions of the casted members. AR Visualization technology will be employed to overlay holographic representations of precast concrete elements onto real-world objects. These holographic representations will be color-coded to indicate which errors are found during construction, and which members should not be utilized in construction, aiding inspectors in quickly identifying deviations from quality standards during fabrication and at the precast plant. They can display the design and error and keep it to compare later. The tasks involved in this project include the following: Task 1: Adapt the AR application to PC inspection requirements; Task 2: Enhance dimensional measurement accuracy across varying lighting conditions; Task 3: Establish a standardized procedure for PC element inspectors utilizing AR and LiDAR.

Language

  • English

Project

  • Status: Active
  • Funding: $160,000.00
  • Contract Numbers:

    CY2-UNM-02

    69A3552348306

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Southern Plains Transportation Center

    University of Oklahoma
    202 W Boyd St, Room 213A
    Norman, OK  United States  73019
  • Project Managers:

    Dunn, Denise

  • Performing Organizations:

    University of New Mexico, Albuquerque

    Department of Civil Engineering
    Albuquerque, NM  United States  87131-0001
  • Principal Investigators:

    Zhang, Su

    Moreu, Fernando

  • Start Date: 20241001
  • Expected Completion Date: 20250930
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01941688
  • Record Type: Research project
  • Source Agency: Southern Plains Transportation Center
  • Contract Numbers: CY2-UNM-02, 69A3552348306
  • Files: UTC, RIP
  • Created Date: Jan 1 2025 5:01PM