• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.16 no.6
• /
• pp.37-42
• /
• 2007

The purpose of this research is stability estimation of plant structure through classification and recognition about welding flaw in SWP(Spiral Welding Pipe). And, In this research, we used nondestructive test based on ultrasonic test as inspection method, and made up 2-axes inspection robot in order to control of ultrasonic probe on the SWP surface, and programmed to image processing and probabilistic neural network(PNN) classifying code by MATLAB programming. Through this process, we proved efficiency on the system of SWP stability Estimation.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.15 no.2
• /
• pp.87-92
• /
• 2006

This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.569-571
• /
• 2010

In this paper, we develop a vision inspection system for inspecting flaws on plastic products such as insufficient moldings, spots, scratches. The inspection algorithm for this system consist of image binarization for curved structure of plastic products, image noise removal using morphology operation, labeling methods for candidate regions and image filtering and calibration method for flaw inspection. In order to improve its performance, we also develop fast image processing algorithm based on GUI. To verify the effectiveness of this system, we conducted evaluation for the system accuracy and the inspection algorithm processing time.