Detection of Three-Dimensional Parameter of Defects for Gas Turbine Blades Based on Two-Dimensional Digital Radiographic Projective Imaging
Source abstract
Abstract
During the manufacturing and service process of turbine blades, various types of defects may be formed and bring huge threat to the safe operation of gas turbine. However, if qualifying the turbine blade only by the existence of defects, it will lead to the unavoidable large waste. Preferably, it should determine whether the turbine blades with defects could be in safe service for some period of time. Therefore, the residual strength and fatigue life should be analyzed and predicted based on the three-dimensional feature of defect, such as size, location. Considering the characteristics of shape (free-from surface) and material (high density superalloy), the radiographic imaging based techniques could be used in the non-destructive testing of turbine blades. For one thing, although the industrial computed tomography can obtain the three-dimensional feature of defects, the low efficiency and high cost may limit its practical application. For another, the projective nature of digital radiographic imaging technique results in the unavailability of geometric parameter in the transmitting direction and brings difficulty to the three-dimensional characterization of defect. Aiming at this critical issue, a new method based on the determination of mapping relationship between the thickness of material and the gray value of image is presented in this paper. By acquiring the thickness of two defects in a gas turbine blade, the three-dimensional geometric parameter (volume) can be calculated. Finally, the accuracy of the proposed method is verified using a test specimen. In comparison with the industrial CT, the proposed method could have relative high efficiency and low cost in the application of the three-dimensional quantitative characterization of defects for gas turbine blades.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Welding Techniques and Residual Stresses · Advanced X-ray and CT Imaging · Thermography and Photoacoustic Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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