3D positioning of defects for gas turbine blades based on digital radiographic projective imaging. (January 2023)

• Record Type: Journal Article
• Authors: Chen, Lei; Li, Bing; Zhang, Lei; Shang, Zhongyu
• Is Part Of: NDT & E international. Volume 133(2023)
• Publication Date: 2023-01
• Subjects: Gas turbine blade -- Defect -- Digital radiography -- Non-destructive testing -- 3D spatial position; Nondestructive testing -- Periodicals; Contrôle non destructif -- Périodiques; Electronic journals; 620.1127
• DOI: 10.1016/j.ndteint.2022.102751
• Languages: English
• ISSNs: 0963-8695

Abstract

Abstract: During the manufacturing and service process of gas turbine blades, various types of defects may be formed and bring huge threat to the safe operation of gas turbine. To confirm whether the gas turbine blades with defects could be in safe service for some period of time, the residual strength and fatigue life of gas turbine blade should be analyzed and predicted based on the 3D spatial position of defect, which significantly determines the degree of effect on the strength of gas turbine blade. Considering the characteristics of shape (free-from surface) and material (high density superalloy), the digital radiographic imaging techniques could be used in the non-destructive testing of gas turbine blades. However, the projective nature of digital radiography (DR) technique results in the unavailability of position in the transmitting direction of X-ray beam and brings difficulty to the 3D characterization of defect. Aiming at this critical issue, based on the exploration of the changing rule for the projection of a point feature relative to the irradiating angle, a new method is presented to obtain the 3D spatial position of defect. Finally, the accuracy of the proposed method is validated using a metrological computed tomography (CT) system. It can be learned that the proposed DR based method could obtain the 3D spatial position of defect with a relative error less than 2%. The 3D spatial position of defect could be used in the following residual strength analysis and fatigue life prediction of gas turbine blade.