Abstract

The pressurizer is one of the critical components in a nuclear reactor, whose main function is to maintain the primary system pressure within specific boundaries. The pressurizer is a large vessel that is made of carbon or low‐alloy steel shell, clad internally with a layer of stainless steel. It works with high temperature, high humidity and high pressure. The crack defects that would probably appear in the internal surface of the vessel must be detected and recorded, as well as changes to any existing known cracks. This paper presents an implementation of a mobile robot, which can sense and transmit the image of the internal surface to a remote analysis center, where the image is processed and recorded. A neural network‐based pattern classifier is employed to assist inspectors to detect the flaws that appear in the surface of the vessel. Because the real‐life defects rarely exist in the pressurizer, the training of the network becomes very difficult. A new algorithm is exploited to solve the problem. General considerations about the robot design are also presented.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.