Signal-to-noise ratio enhancement based on wavelet filtering in ultrasonic testing

Area of Science:

• Materials Science
• Signal Processing
• Non-Destructive Testing

Background:

• Coarse-grained materials in ultrasonic non-destructive testing (NDT) suffer from backscattering noise.
• This noise originates from grain scattering, obscuring critical flaw echo signals.
• Existing filtering methods aim to improve the signal-to-noise ratio (SNR) in NDT.

Purpose of the Study:

• To comparatively evaluate wavelet transform-based filtering methods for ultrasonic NDT.
• To assess the efficacy of stationary, discrete, and wavelet packet de-noising techniques.
• To enhance the signal-to-noise ratio in ultrasonic signals affected by grain scattering.

Main Methods:

• Utilized wavelet transform techniques including stationary, discrete, and wavelet packet de-noising.
• Employed both measured and simulated ultrasonic signals for method validation.
• Evaluated de-noising performance using signal-to-noise ratio enhancement.
• Assessed filtering efficiency specific to ultrasonic flaw detection.

Main Results:

• Wavelet packet de-noising demonstrated superior performance in the experimental setup.
• Significant improvements in signal-to-noise ratio were achieved across tested methods.
• The study verified the effectiveness of wavelet-based de-noising on ultrasonic signals.
• Wavelet packet de-noising showed the highest filtering efficiency for ultrasonic NDT.

Conclusions:

• Wavelet packet de-noising is a highly effective method for mitigating grain scattering noise in ultrasonic NDT.
• This technique significantly improves the detection of material flaws by enhancing signal clarity.
• The findings support the adoption of wavelet packet de-noising for improved ultrasonic inspection of coarse-grained materials.