• Lecture time: Friday: 09:30:00 - 10:20:00 ET
  • Lab time: Monday: 09:30:00 - 11:20:00 ET
  • Domain: Aerospace
  • Keywords: Anomaly Identification, Image Processing, Machine Learning
  • Tools: Machine Learning, Python
  • Citizenship: Open to all students
Summary

Turbine blades and vanes are analyzed via X-Ray imaging methods to detect internal non-metallic anomalies. Howmet would like the students to develop a machine learning algorithm and image process system that can automatically and correctly identify anomalies in these X-Ray images

Description

Please see the PDF for a detailed project description. When registering for this project in UniTime, look for 'Howmet Aerospace (Image Process System)' in the Note section, and select the appropriate CRN.