ArticleSensors (Basel, Switzerland)2021
Assessment of the Effect of Cleanliness on the Visual Inspection of Aircraft Engine Blades: An Eye Tracking Study.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
The trial behind it
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Who cites it
3 citing papers in PubMed, 28 citations in OpenAlex.
- A Visual Attention Analysis Method for Industrial Patrol Inspection Based on Eye Tracking and Deep Learning.Sensors (Basel, Switzerland) · 2026Article
- PoseNeRF: In Situ 3D Reconstruction Method Based on Joint Optimization of Pose and Neural Radiation Field for Smooth and Weakly Textured Aeroengine Blade.Sensors (Basel, Switzerland) · 2025Article
- Evaluation of expert skills in refinery patrol inspection: visual attention and head positioning behavior.Heliyon · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Background-The visual inspection of aircraft parts such as engine blades is crucial to ensure safe aircraft operation. There is a need to understand the reliability of such inspections and the factors that affect the results. In this study, the factor 'cleanliness' was analysed among other factors. Method-Fifty industry practitioners of three expertise levels inspected 24 images of parts with a variety of defects in clean and dirty conditions, resulting in a total of N = 1200 observations. The data were analysed statistically to evaluate the relationships between cleanliness and inspection performance. Eye tracking was applied to understand the search strategies of different levels of expertise for various part conditions. Results-The results show an inspection accuracy of 86.8% and 66.8% for clean and dirty blades, respectively. The statistical analysis showed that cleanliness and defect type influenced the inspection accuracy, while expertise was surprisingly not a significant factor. In contrast, inspection time was affected by expertise along with other factors, including cleanliness, defect type and visual acuity. Eye tracking revealed that inspectors (experts) apply a more structured and systematic search with less fixations and revisits compared to other groups. Conclusions-Cleaning prior to inspection leads to better results. Eye tracking revealed that inspectors used an underlying search strategy characterised by edge detection and differentiation between surface deposits and other types of damage, which contributed to better performance.
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Registered trials
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.