Non-destructive erosive wear monitoring of multi-layer coatings using AI-enabled differential split ring resonator based system

Author:

Balasubramanian Vishal,Niksan Omid,Jain Mandeep C.ORCID,Golovin KevinORCID,Zarifi Mohammad H.ORCID

Abstract

AbstractUnprotected surfaces where a coating has been removed due to erosive wear can catastrophically fail from corrosion, mechanical impingement, or chemical degradation, leading to major safety hazards, financial losses, and even fatalities. As a preventive measure, industries including aviation, marine and renewable energy are actively seeking solutions for the real-time and autonomous monitoring of coating health. This work presents a real-time, non-destructive inspection system for the erosive wear detection of coatings, by leveraging artificial intelligence enabled microwave differential split ring resonator sensors, integrated to a smart, embedded monitoring circuitry. The differential microwave system detects the erosion of coatings through the variations of resonant characteristics of the split ring resonators, located underneath the coating layer while compensating for the external noises. The system’s response and performance are validated through erosive wear tests on single- and multi-layer polymeric coatings up to a thickness of 2.5 mm. The system is capable of distinguishing which layer is being eroded (for multi-layer coatings) and estimating the wear depth and rate through its integration with a recurrent neural network-based predictive analytics model. The synergistic combination of artificial intelligence enabled microwave resonators and a smart monitoring system further demonstrates its practicality for real-world coating erosion applications.

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry,Multidisciplinary

Reference55 articles.

1. Stachowiak, G. W. & Batchelor, A. W. Engineering Tribology 4th edn (Elsevier, 2013).

2. Obanijesu, E. O., Pareek, V., Gubner, R. & Tade, M. O. Corrosion education as a tool for the survival of natural gas industry. Nafta 61, 555–563 (2010).

3. Hansson, C. M. in Corrosion of Steel in Concrete Structures (ed. Poursaee, A.) 3–18 (Elsevier, 2016).

4. Invernizzi, S., Montagnoli, F. & Carpinteri, A. Fatigue assessment of the collapsed XXth century cable-stayed Polcevera Bridge in Genoa. Proc. Struct. Integr. 18, 237–244 (2019).

5. Koch, G. H., Brongers, M. P. H., Thompson, N. G., Paul Virmani, Y. & Payer, J. H. Corrosion cost and preventive strategies in the United States [Final report]. http://impact.nace.org/documents/ccsupp.pdf (2002).

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