INSPECTION OF INTERNAL SURFACE OF CYLINDRICAL STRUCTURES

VAlue proposition

Surface defect inspection, detection, and classification in hollow cylindrical surfaces such as pipes and barrels have a significant impact on the structural integrity of various industrial products. Regular inspection and identification of the faults reduces the likelihood of faults’ aggravation, limits the damaging effects, and increases the product life. However, most of the defect detection systems for cylindrical surfaces rely heavily on handcrafted feature extraction limiting the ability to recognize the defects effectively. An image processing-based automatic defect detection technology for cylindrical hollow surfaces benefits the inspection process.

 

Description of Technology

The technology has a set of 3D structured light-based imaging tools that are designed for the inspection of the internal surfaces of cylindrical entities. The main novelties in this technology are: 1) Miniaturization of a sensor that is capable of sequential endoscopic structured light sensing, 2) A side-by-side sensor design with 360-degree unobstructed inspection capability, 3) A phase sensor with the capability to exploit the sensor movement to enhance the 3D reconstructed profile, 4) An algorithm to automatically calibrate the projection module when the sensor is placed inside a cylindrical environment with known diameter, 5) An electronic stabilization algorithm to register the consecutive frames from the sensor and reconstruct the pipe 3D profile. The tools are capable of providing inspection capability of the internal pipe surface while maintaining a small sensor footprint to allow insertion in small diameter pipelines.

 

Benefits

  • 360-degree unobstructed view
  • Automatic calibration
  • Reconstruct 3D profile

 

Applications

  • Pipeline inspection
  • Small diameter pipes
  • Internal surfaces of cylindrical entities

 

IP Status

Patent Pending

 

LICENSING RIGHTS AVAILABLE

Full licensing rights available

 

INVENTORS: Yiming Deng, Mohand Alzuhiri

 

Tech ID: TEC2022-0156

 

Patent Information: