An improved local mean decomposition method based on improved composite interpolation envelope and its application in...

Area of Science:

• Signal Processing
• Mechanical Engineering
• Fault Diagnosis

Background:

• The standard Compound Interpolation Envelope (CIE) method in Local Mean Decomposition (LMD) suffers from non-adaptive threshold selection, impacting decomposition performance.
• Accurate signal decomposition is crucial for identifying faults in rotating machinery like rolling bearings.

Purpose of the Study:

• To develop an improved Local Mean Decomposition (LMD) method that overcomes the limitations of the standard CIE.
• To enhance the analysis of complex signals, specifically for rolling bearing fault detection.

Main Methods:

• An improved envelope processing method, Improved Compound Interpolation Envelope (ICIE), is proposed by integrating CIE with fractal box dimension.
• An enhanced LMD method, termed ICIELMD, is developed by incorporating the ICIE method.
• Comparative experiments were conducted using simulation signals and real-world rolling bearing datasets (CWRU and NASA).

Main Results:

• The proposed ICIELMD method demonstrates comparable or superior performance to existing state-of-the-art methods (CIELMD).
• The experimental results validate the effectiveness of ICIELMD in decomposing complex signals.
• ICIELMD shows significant potential for analyzing rolling bearing fault data.

Conclusions:

• The ICIELMD method offers a robust solution for overcoming the limitations of traditional LMD techniques in non-stationary signal analysis.
• This improved method provides a valuable tool for accurate rolling bearing fault diagnosis, enhancing machinery health monitoring.