Evaluation of Influence Factors on the Visual Inspection Performance of Aircraft Engine Blades

Jonas Aust,Antonija Mitrovic,Dirk Pons

doi:10.3390/aerospace9010018

Abstract

Background—There are various influence factors that affect visual inspection of aircraft engine blades including type of inspection, defect type, severity level, blade perspective and background colour. The effect of those factors on the inspection performance was assessed. Method—The inspection accuracy of fifty industry practitioners was measured for 137 blade images, leading to N = 6850 observations. The data were statistically analysed to identify the significant factors. Subsequent evaluation of the eye tracking data provided additional insights into the inspection process. Results—Inspection accuracies in borescope inspections were significantly lower compared to piece-part inspection at 63.8% and 82.6%, respectively. Airfoil dents (19.0%), cracks (11.0%), and blockage (8.0%) were the most difficult defects to detect, while nicks (100.0%), tears (95.5%), and tip curls (89.0%) had the highest detection rates. The classification accuracy was lowest for airfoil dents (5.3%), burns (38.4%), and tears (44.9%), while coating loss (98.1%), nicks (90.0%), and blockage (87.5%) were most accurately classified. Defects of severity level S1 (72.0%) were more difficult to detect than increased severity levels S2 (92.8%) and S3 (99.0%). Moreover, visual perspectives perpendicular to the airfoil led to better inspection rates (up to 87.5%) than edge perspectives (51.0% to 66.5%). Background colour was not a significant factor. The eye tracking results of novices showed an unstructured search path, characterised by numerous fixations, leading to longer inspection times. Experts in contrast applied a systematic search strategy with focus on the edges, and showed a better defect discrimination ability. This observation was consistent across all stimuli, thus independent of the influence factors. Conclusions—Eye tracking identified the challenges of the inspection process and errors made. A revised inspection framework was proposed based on insights gained, and support the idea of an underlying mental model.

Highlights

Aircraft engine components are subject to various internal and external factors such as vibration, high temperatures, rotational speed, rubbing, corrosion, and foreign objects debris (FOD)
Visual inspection is the most common check-up of aircraft engines, as it accounts for 90% of all non-destructive testing (NDT) [2,3]
The first factor that was analysed is the type of inspection, i.e., borescope and piece-part inspection

Summary

Introduction

Aircraft engine components are subject to various internal and external factors such as vibration, high temperatures, rotational speed, rubbing, corrosion, and foreign objects debris (FOD). There are various influence factors that affect visual inspection of aircraft engine blades including type of inspection, defect type, severity level, blade perspective and background colour. The effect of those factors on the inspection performance was assessed. A generalised linear/non-linear logit model around inspection accuracy with Background Colour, Expertise, Previous Inspection Experience, Education, and Visual Acuity as categorical factors and Work Experience as the continuous predictor confirmed that none of the demographical factors was significant. This might explain why there was a tendency towards less findings on yellow backgrounds, as well as for defective blades, not significant

Results

Discussion

Conclusion