Digital Signal Processing Methods for Ultrasonic Echoes.

Area of Science:

• Digital Signal Processing
• Ultrasonic Testing
• Data Analysis

Background:

• Accurate ultrasonic thickness measurements rely heavily on signal-to-noise ratio.
• Traditional band-pass filters are insufficient for reducing noise in industrial ultrasonic applications.
• Advanced filtering techniques are needed for reliable signal recovery.

Purpose of the Study:

• To evaluate the effectiveness of total variation and Tikhonov regularization methods for filtering acoustic and ultrasonic signals.
• To compare regularization methods against traditional frequency-based filtering.
• To demonstrate noise reduction capabilities for improved ultrasonic thickness measurements.

Main Methods:

• Application of total variation and Tikhonov regularization techniques.
• Filtering of digitally produced and transducer-generated acoustic and ultrasonic signals.
• Comparison with frequency-based filtering methods.
• Parameter optimization for signal-to-noise ratio enhancement.

Main Results:

• Total variation and Tikhonov filters accurately recover signals from noisy data faster than band-pass filters.
• The total variation filter significantly reduces noise in ultrasonic signals with clear echoes.
• Signal-to-noise ratios were improved by over 400% through parameter optimization.

Conclusions:

• Regularization methods, particularly total variation, offer a more efficient approach to noise reduction in ultrasonic systems compared to frequency-based filtering.
• These methods enable more reliable and accurate ultrasonic thickness measurements in industrial settings.
• The study highlights the potential of advanced signal processing for enhancing critical industrial measurements.