Signal feature extraction of aero-engine turbine blade crack detection

Xia Yu*, Wei Min Zhang, Zhong Chao Qiu, Guo Long Chen, Dun Hui Zhao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

The aero-engine turbine blade is a high precision part. Blade surface crack detection belongs to an irregular surface detection, and is a hotspot and difficulty in the field of non-destructive testing. Taking the unique advantage of eddy current testing into account, a simple, practical and effective differential incentive eddy current probe is designed to detect the prefabricated micro-cracks of aero-engine turbine blades. Since the surface curvature of turbine blade varies, the lift-off effect exists inevitably in the detection process. Therefore, the test results of the detection signal contain noise and multiple singular points. In order to ensure that the important information of defect location is not lost, the combination of the mirror extension empirical mode decomposition (EMD) reconstruction and wavelet singularity detection method is used to process the detected micro-crack signals, filter out the influence of several distortion points on non-cracked positions, and achieve an accurate and effective determination of the micro-crack position of turbine blade. The results show that the method can effectively reduce the noise and interference of detection signal, and extract accurately the feature information of crack signal.

Original languageEnglish
Pages (from-to)1267-1274
Number of pages8
JournalBinggong Xuebao/Acta Armamentarii
Volume35
Issue number8
DOIs
Publication statusPublished - 1 Aug 2014

Keywords

  • Aero-engine turbine blade
  • Aerospace system engineering
  • Micro-crack
  • Mirror extension EMD
  • Wavelet singularity

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