The Research Of Identification Methods For Tiny Flaw In Superalloy Using Ultrasonic Testing

Because aeroengines work in harsh environments such as high temperature and high pressure,engines have extremely high demands on the materials they manufacture,and even minor defects can cause serious accidents that cause machine crashes.The coarse-grained superalloy materials have been widely used in aircraft engine manufacture because of their high strength,fatigue resistance,and high temperature resistance.However,the average grain size of the coarse-grained superalloy materials is large,and the conventional ultrasonic detection technology will cause serious scattering when it is detected.The severe background noise generated will greatly affect the signal-to-noise ratio of the ultrasonic detection signal.,it is difficult to identify the flaw echo.Therefore,it is very important to study the detection and identification methods of tiny defects of coarse-grained superalloys.This dissertation focuses on the ultrasonic detection and identification method of tiny defects in coarse-grained high-temperature alloys.It uses the characteristics of the defect and the nonlinear frequency response characteristics of the ultrasonic flaws to identify and analyze the defects,and proposes a new rough.Crystal superalloy material tiny defects identification method,and made some innovative results.The main work of this article is as follows:First of all,theoretical analysis is made on the difficulties and significance of detection of tiny defects in coarse-grained superalloy materials.The influence of tiny defects on the law of acoustic propagation was studied,and the identification of tiny defects using the characteristics of acoustic diffraction and nonlinear response was determined.Secondly,using the ABAQUS finite element simulation software to simulate the diffraction propagation law of the sound model,the flat bottom hole model and the small defect model.And simulate the ultrasonic nonlinear response in the tiny flaw model.Finally,a series of flat-bottom hole defects and a cross-hole defect were designed and manufactured in the test piece.The simulation results were first checked in the A-scan experiment.The optimal probe and system parameter settings were selected to detect and identify artificial defects in the feature scanning surface imaging detection system and nonlinear detection system.In combination with the phased array,fast depth positioning is achieved on the recognition result.The research results show that the tiny flaws have scattering phenomenon and nonlinear response characteristics to the propagation of acoustic waves.By using the first and second wave trains that receive the bottom of the bottom wave to perform amplitude imaging,the detection accuracy at the grain size can identify ?0.1 mm flat bottom hole defects,and the bottom wave dominant frequency is within a certain range along with defects.The increase decreases and decreases as the depth of burial increases.Compared with bottom-wave amplitude imaging,it is easier to identify defects and the image is clear.A finite-aperture nonlinear ultrasonic inspection method is used to identify ?0.1mm flat bottom hole defects.In combination with the advantages of phased array on the basis of plane recognition defects,the fast deep positioning of ?0.3mm flat-bottomed hole defects is realized.