Case Study
Artificial Intelligence For Ultrasonic Pipe Inspection
This solution was developed as a proof of concept for a large nuclear operator in Ontario to automate the detection of fuel channel defects. Introduction Pipe-inspection is a critical aspect of the operation of plants. Over the years, pipes can get damaged from scratches, rusting, cracking, corrosion and sagging. A large nuclear operator in Ontario approached Alithya to build a tool that can automatically detect wear-induced flaws in the plant’s fuel channels. CHALLENGES > The client’s processes require multiple streams of highly skilled analysts to review the collected ultrasonic (UT) data. > Identification and sizing of fuel channel defects is a manual, subjective process, which requires a significant time investment. > Recent inspection tooling modifications have introdu