Key Engineering Materials Vols. 413-414

Abstract: Endoscopy is an important non-destructive testing (NDT) method. It plays an important role in damage assessment and fault detection for aeroengine and structure [1,3]. However, the endoscopy usually relies on the operator’s experience to measure the defects manually in the application. Therefore, the current endoscopy method has some shortcomings that the accuracy and the efficiency of its measurement are low. To solve these problems, an automatic image measurement method based on the cubic spline interpolation is proposed in this paper. Firstly, the endoscopy image pre-processing such as gray processing, filtering, sharpening, segmentation and edge extraction are presented. Then, the pixel points in the processed edge image are handled by cubic spline interpolation and the spline function is got. After the starting point, vertex and endpoint of the defect are determined automatically, the width, depth and distance of defects are worked out. Finally, the method is applied in the fault detection for aeroengine’s blade. The experimental results show that this method can detect the width, depth and distance of the aeroengine’s blade defects exactly and quickly.

Abstract: This paper presents the use of the MUSIC algorithm improved by higher order statistics (HOS) to extract key features from the noisy acoustic emission (AE) signals. The low signal-to-noise ratio of AE signals has been identified as a main barrier to the successful condition monitoring of pump mechanical seals. Since HOS methods can effectively eliminate Gaussian noise, it is possible in theory to identify a change in seal conditions from AE measurements even with low signal-to-noise ratios. Tests conducted on a test rig show that the developed algorithm can successfully detect the AE signal generated from the friction of seal faces under noisy conditions.