An improved low-frequency noise reduction method in shock wave pressure measurement based on mode classification and...

Area of Science:

• Signal Processing
• Acoustics
• Measurement Science

Background:

• Shock Wave Pressure (SWP) measurement is often ill-posed due to low-frequency noise interference.
• Existing methods struggle to accurately filter noise without compromising signal integrity.

Purpose of the Study:

• To develop an improved noise-filtering method for SWP measurement signals.
• To enhance the accuracy and reliability of SWP data acquisition.

Main Methods:

• Proposed Recursive Empirical Mode Decomposition (REMD) for adaptive signal decomposition.
• Developed a mode classification scheme based on energy gradient and ringing amplitude ratio.
• Utilized adaptive diminishing white noise-assisted technology for iterative component extraction.

Main Results:

• REMD effectively filters low-frequency noise from SWP signals.
• Simulated and real-world experiments show REMD yields superior Signal-to-Noise Ratio (SNR), lower Root Mean Square Error (RMSE), and lower Percent Range Difference (PRD).
• The method demonstrated significant improvements in denoising ability and signal integrity compared to existing approaches.

Conclusions:

• The proposed REMD method offers a robust solution for accurate SWP measurement.
• REMD enhances the reliability of SWP data, crucial for various scientific and engineering applications.
• This technique improves upon existing methods for noise reduction in complex measurement signals.