Evidence map›Paper›PMID 37582844›Full record

ArticleNature communications2023

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

Vishal Balasubramanian, Omid Niksan, Mandeep C Jain, Kevin Golovin, Mohammad H Zarifi

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Vishal BalasubramanianOkanagan MicroElectronics and Gigahertz Applications Laboratory, School of Engineering, Faculty of Applied Science, University of British Columbia, Kelowna, BC, V1V 1V7, Canada.
Omid NiksanOkanagan MicroElectronics and Gigahertz Applications Laboratory, School of Engineering, Faculty of Applied Science, University of British Columbia, Kelowna, BC, V1V 1V7, Canada.
Mandeep C JainOkanagan MicroElectronics and Gigahertz Applications Laboratory, School of Engineering, Faculty of Applied Science, University of British Columbia, Kelowna, BC, V1V 1V7, Canada.ORCID http://orcid.org/0000-0003-4105-8711
Kevin GolovinDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, M5S 3G8, Canada.ORCID http://orcid.org/0000-0001-8309-7458
Mohammad H ZarifiOkanagan MicroElectronics and Gigahertz Applications Laboratory, School of Engineering, Faculty of Applied Science, University of British Columbia, Kelowna, BC, V1V 1V7, Canada. mohammad.zarifi@ubc.ca.ORCID http://orcid.org/0000-0001-5544-3966

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unprotected 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.

Identifiers

PMID37582844
PMCPMC10427693

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.