Industrial Application of AI-Based Assistive Magnetic Particle Inspection

Author:

Baumeyer Julien12ORCID,Chatoux Hermine2ORCID,Pelletier Arnaud1ORCID,Marquié Patrick2ORCID

Affiliation:

1. CMPhy, 26 Rue Paul Sabatier, 71530 Crissey, France

2. Laboratoire ImViA Dijon, 64 Rue Sully, 21000 Dijon, France

Abstract

Magnetic Particle Inspection (MPI) is one of the most used methods in Non-Destructive Testing (NDT), allowing precise and robust defect detection on industrial-grade manufactured parts. However, human controllers perform this task in full black environments under UV-A lighting only (with safety glasses) and use chemical products in a confined environment. Those constraints tends to lower control performance and increase stress and fatigue. As a solution, we propose an AI-based assistive machine (called “PARADES”) inside the hazardous environment, remotely manipulated by a human operator, outside of the confined area, in cleaner and safer conditions. This paper focuses on the development of a complete industrial-grade AI machine, both in terms of hardware and software. The result is a standalone assistive AI-based vision system, plug-and-play and controller-friendly, which only needs the usual power supply 230 V plug that detects defects and measures defect length. In conclusion, the PARADES machines address for the first time the problem of occupational health in MPI with an industrial standalone machine which can work on several parts and be integrated into current production lines. Providing cleaner and healthier working conditions for operators will invariably lead to increased quality of detection. These results suggest that it would be beneficial to spread this kind of AI-based assistive technology in NDT, in particular MPI, but also in Fluorescent Penetrant Testing (FPT) or in visual inspection.

Funder

Agence Nationale de la Recherche

Publisher

MDPI AG

Reference25 articles.

1. Advances and Researches on Non Destructive Testing: A Review;Dwivedi;Mater. Today Proc.,2018

2. Smallbone, C. (2012, January 16–20). Welding and NDT—Enabling technologies to improve the global quality of life. Proceedings of the 18th World Conference on Nondestructive Testing, Durban, South Africa.

3. Pelletier, A., Crepeau, A., Lemond, J., Marquié, P., Baumeyer, J., and Chatoux, H. (2023). Robotisation et Numérisation pour la Magnétoscopie et le Ressuage. e-J. Nondestruct. Test., 28.

4. A machine vision assisted system for fluorescent magnetic particle inspection of railway wheelsets;Ma;Proc. AIP Conf. Proc.,2016

5. Willcox, M. (2000). Automatic Defect Recognition in Magnetic Particle Inspection Applications, Insight NDT Equipment Ltd.

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