Vision-based damage detection of aircraft engine’s compressor blades

Abstract

In this paper, a new vision-based method for an evaluation of aircraft engine's compressor turbine blade damage is presented. The algorithm developed in the research uses image processing and analysis techniques for detection, localization and evaluation of the extent of compressor blades' damage. An introduction of local pixel intensity standard deviation image (SDI) computed for each image pixel made it possible to perform a correct image binarization and damage detection even for images taken in poor lighting conditions and corrupted by specular reflections, shadows and micro reflections from blade’s surface roughness. Fractal dimension (FD) analysis of the blade's edge has been applied for automatic localization of detected damage along the blade’s edge. An extraction of damage for computation of its geometrical dimensions was carried out with a help of binary image convex hull complement. The performance and accuracy of the developed method was compared with other image analysis methods. Hough transform for marker detection has been used as a method for scaling. The application of the developed measurement tool may be a useful aid in diagnostic inspections of aircraft engines using endoscopic cameras.

Keywords

• aircraft engine
• image processing
• compressor blade diagnostics
• vision-based damage detection