Improved Adaptive Multipoint Optimal Minimum Entropy Deconvolution and Application on Bearing Fault Detection in
Yu Wei1, Yuanbo Xu1, Yinlong Hou1
1School of Automation, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.
Entropy (Basel, Switzerland)
|August 26, 2023
Summary
This study introduces an improved adaptive multipoint optimal minimum entropy deconvolution (IAMOMED) method for detecting bearing faults. IAMOMED effectively identifies fault characteristics in vibration signals corrupted by random impulsive noise, outperforming traditional methods.
Area of Science:
- Mechanical Engineering
- Signal Processing
- Condition Monitoring
Background:
- Random impulsive noise, characterized by non-Gaussianity, challenges traditional bearing fault diagnosis methods.
- Common noise reduction techniques are often ineffective against the distinct features of impulsive noise.
Purpose of the Study:
- To develop a robust method for bearing fault detection in the presence of significant random impulsive noise.
- To enhance the applicability and effectiveness of minimum entropy deconvolution for rotating machinery diagnostics.
Main Methods:
- An improved adaptive multipoint optimal minimum entropy deconvolution (IAMOMED) was developed.
- Envelope autocorrelation function was used for automatic cyclic impulse period estimation.
- Particle swarm optimization determined the optimal filter length.
Main Results:
- The proposed IAMOMED effectively identified bearing fault features from noisy vibration signals.
- Contrast experiments confirmed IAMOMED's superiority over the original MOMED in impulsive noise environments.
- Accurate diagnosis of fault types was achieved using the IAMOMED technique.
Conclusions:
- IAMOMED offers a more suitable approach for bearing fault detection under random impulsive noise conditions.
- The method provides a viable alternative for fault detection in rotating machinery.
- The enhancements improve practical applicability and diagnostic accuracy.
Keywords:
envelope autocorrelation functionfault characteristic detectionmultipoint optimal minimum entropy deconvolutionparticle swarm optimizationrandom impulsive noiserolling element bearingMore Related Videos
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