Abstract
The Acoustic Emission (AE) is a widely used real-time monitoring technique for the deformation damage and crack initiation of areo-engine blades. In this work, a tensile test for TC11 titanium alloy, one of the main materials of aero-engine, was performed. The AE signals from different stages of this test were collected. Then, the AE signals were decomposed by the Variational Mode Decomposition (VMD) method, in which the signals were divided into two different frequency bands. We calculated the engery ratio by dividing the two different frequency bands to characterize TC11′s degree of deformation. The results showed that when the energy ratio was −0.5 dB, four stages of deformation damage of the TC11 titanium alloy could be clearly identified. We further combined the calculated Partial Energy Ratio (PER) and Weighted Peak Frequency (WPF) to identify the crack initiation of the TC11 titanium alloy. The results showed that the identification accuracy was 96.33%.
Highlights
Aero-engines, the “heart” of airplanes, are large-scale power equipments, which require a high reliability to function
The results showed that when the energy ratio was −0.5 dB, four stages of deformation damage of the TC11 titanium alloy could be clearly identified
This was due to thetitanium simultaneous the majority of the Acoustic Emission (AE) signal energy ratio was greater than −0.5
Summary
Aero-engines, the “heart” of airplanes, are large-scale power equipments, which require a high reliability to function. In the current maintenance protocols of aero-engines, the commonly used approaches for detecting blade deformation and cracks are the thermal infrared test method [5], ultrasonic method [6], endoscope method [7], and grating method [8]. Swit and Lu Chao applied the time-frequency analysis method to process the AE signals from composite materials in order to estimate the damage process and degree of material degradation [23,24]. The Variable Mode Decomposition (VMD) has the ability of determining the frequency center and bandwidth of the decomposed component by iteratively searching the optimal solution of the variational model It can adaptively decompose the nonstationary signals with strong noise resistance and no modal aliasing [28,29]. The results showed that the method could provide real-time monitoring over the aero-engine blade cracks
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
