The purpose of this research is to develop a new means of identifying and extracting geometrical feature statistics from a
non-contact precision-measurement 3D profilometer. Autonomous algorithms have been developed to search through
large-scale Cartesian point clouds to identify and extract geometrical features. These algorithms are developed with the
intent of providing real-time production quality control of cold-rolled steel wires. The steel wires in question are prestressing
steel reinforcement wires for concrete members. The geometry of the wire is critical in the performance of the
overall concrete structure.
For this research a custom 3D non-contact profilometry system has been developed that utilizes laser displacement
sensors for submicron resolution surface profiling. Optimizations in the control and sensory system allow for data points
to be collected at up to an approximate 400,000 points per second. In order to achieve geometrical feature extraction and
tolerancing with this large volume of data, the algorithms employed are optimized for parsing large data quantities. The
methods used provide a unique means of maintaining high resolution data of the surface profiles while keeping algorithm
running times within practical bounds for industrial application.
By a combination of regional sampling, iterative search, spatial filtering, frequency filtering, spatial clustering, and
template matching a robust feature identification method has been developed. These algorithms provide an autonomous
means of verifying tolerances in geometrical features. The key method of identifying the features is through a
combination of downhill simplex and geometrical feature templates. By performing downhill simplex through several
procedural programming layers of different search and filtering techniques, very specific geometrical features can be
identified within the point cloud and analyzed for proper tolerancing. Being able to perform this quality control in real
time provides significant opportunities in cost savings in both equipment protection and waste minimization.