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Lamb Wave-Based Damage Localization Feature Enhancement and Extraction Method for Stator Insulation of Large
1Department of Electrical Engineering, Tongji University, Shanghai 201804, China.
Sensors (Basel, Switzerland)
|August 1, 2020
Summary
This study introduces a novel method using variational mode decomposition (VMD) and wavelet transform to accurately locate stator insulation damage in large generators, even in noisy environments. The technique enhances signal quality, improving damage detection accuracy for non-destructive testing.
Area of Science:
- Engineering
- Materials Science
- Signal Processing
Background:
- Lamb waves are crucial for detecting stator insulation damage in large generators.
- Extracting Lamb wave signal features in noisy environments is challenging, reducing damage localization accuracy.
Purpose of the Study:
- To propose a robust method for enhancing Lamb wave signals and extracting damage location features in stator insulation of large motors.
- To improve the accuracy of non-destructive testing for stator insulation damage in complex, noisy environments.
Main Methods:
- Utilized variational mode decomposition (VMD) for signal decomposition, denoising, and reconstruction to mitigate noise sensitivity.
- Applied wavelet transform to the reconstructed signal to extract time of flight (TOF) features of scattered waves for damage localization.
Main Results:
- The VMD and wavelet transform method significantly improved the signal-to-noise ratio of Lamb wave detection signals.
- Experimental verification demonstrated enhanced accuracy in locating stator insulation damage under strong background noise.
Conclusions:
- The proposed VMD and wavelet transform method effectively enhances Lamb wave signal detection and damage localization accuracy in challenging environments.
- This study expands the application of Lamb wave-based non-destructive testing for stator insulation in complex industrial settings.
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