A new visual method for inner-diameter of pipe figure components

In order to measure the inner-diameter of pipe figure components rapidly and efficiently, a new high accurate method based on computer vision was introduced. The new visual measurement method was comprised of two phases, which were capturing cloud data of generatrix and processing cloud data of generatrix. The first phase employed the LMS (Laser Multi-spots Scanning) method, which combined the merits of the LSS (Laser Single-spot Scanning) method, the IRLS (Integrated Ringy Laser Section) method, the DRLS (Distributed Ringy Laser Section) method and the DRDL (Distributed Ringy Discrete Laser-spot) method, and overcame the faults of these methods. The second phase introduced the generatrix resample technology and the symmetrical generatrix difference technology. In this paper, the visual measuring arm based on the LMS method was designed in the beginning. Then, according to the optical structure of the visual measuring arm, a 3D real time mathematic model was developed. Lastly, the data processing technology proposed was adopted to process the cloud data of generatrix. The measurement system based on the new method could complete the measurement of inner-diameter of pipe figure components rapidly and efficiently in experiments, demonstrated good stability, and got high precision.

[1]  Kaspar Althoefer,et al.  State of the art in sensor technologies for sewer inspection , 2002 .

[2]  Kaspar Althoefer,et al.  An ultrasonic profiling method for sewer inspection , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[3]  J. Rheinländer,et al.  Using film density variations for determination of pipe thickness variation in γ-ray radiography , 1995 .

[4]  R. D. Roberts Laser profilometry as an inspection method for reformer catalyst tubes , 1999 .

[5]  Wei Tao,et al.  A new structured-laser-based system for measuring the 3D inner-contour of pipe figure components , 2007 .

[6]  Kaspar Althoefer,et al.  Automated Pipe Defect Detection and Categorization Using Camera/Laser-Based Profiler and Artificial Neural Network , 2007, IEEE Transactions on Automation Science and Engineering.

[7]  Richard P. Stanley Magnetic methods for wall thickness measurement and flaw detection in ferromagnetic tubing and plate , 1996 .

[8]  Kaspar Althoefer,et al.  Pipe inspection using a laser-based transducer and automated analysis techniques , 2003 .

[9]  Masaru Watanabe,et al.  Optical inspection system for the inner surface of a pipe using detection of circular images projected by a laser source , 1994 .

[10]  J. Oksman,et al.  A Parametric Estimation Approach for Groove Dimensioning Using Remote Field Eddy Current Inspection , 1999 .

[11]  M. Hartrumpf,et al.  Optical three-dimensional measurements by radially symmetric structured light projection. , 1997, Applied optics.