Comparison of denoising schemes and dimensionality reduction techniques for fault diagnosis of rolling element bearing using wavelet transform

Mathematics

• Fault Diagnosis 100%
• Dimensionality Reduction 83%
• Denoising 83%
• Wavelet Transform 74%
• Vibration Signal 62%
• Kernel PCA 54%
• Principal Component Analysis 51%
• Defects 48%
• Artificial Neural Network 41%
• Kernel Principal Component Analysis 25%
• Discrete Wavelet Transform 23%
• Wavelets 14%
• Prediction 12%
• Ball 12%
• Evaluation 11%
• Dependent 10%
• Interval 9%

Engineering & Materials Science

• Roller bearings 71%
• Dimensionality reduction 70%
• Principal component analysis 60%
• Wavelet transforms 59%
• Failure analysis 55%
• Singular value decomposition 49%
• Defects 32%
• Neural networks 19%
• Discrete wavelet transforms 17%