Real-Time Prediction of Wear Morphology and Coefficient of Friction Using Acoustic Signals and Deep Neural Networks in a Tribological System
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sample Preparation and Tribological Testing
2.2. Wear Measurement and Finite Element Modeling
2.3. Deep Neural Network Model Development
3. Results
3.1. Surface Roughness Before Wear Testing
3.2. Coefficient of Friction
3.3. Noise Signal Analysis
3.3.1. Time-Domain Signal (First 1 s)
3.3.2. Power Spectral Density (PSD) Analysis
3.3.3. Spectrogram Analysis
3.3.4. One-Third Octave Band Analysis
3.3.5. Accumulative Average Sound Pressure
3.4. Mesh-Independent Validation and Deep Neural Network Training
3.5. Wear and COF Prediction
3.6. Strengths and Limitations of the Proposed Approach
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Material | Density (kg/m3) | Young’s Modulus (Pa) | Poisson’s Ratio |
---|---|---|---|
Steel | 7860 | 1.9984 × 1011 | 0.24 |
Brass | 8469.3 | 9.8 × 1010 | 0.32 |
Type | Grit Size | (m) | (m) | (m) | Average (m) |
---|---|---|---|---|---|
Pin | 240 | 0.4744 | 0.484 | 0.386 | 0.4483 |
Pin | 800 | 0.207 | 0.245 | 0.366 | 0.2393 |
Pin | 1200 | 0.0894 | 0.083 | 0.100 | 0.0911 |
Disc | N/A | 0.7431 | 0.912 | 0.883 | 0.8464 |
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Tian, Y.; Zheng, B.; Khan, M.; Yang, Y. Real-Time Prediction of Wear Morphology and Coefficient of Friction Using Acoustic Signals and Deep Neural Networks in a Tribological System. Processes 2025, 13, 1762. https://doi.org/10.3390/pr13061762
Tian Y, Zheng B, Khan M, Yang Y. Real-Time Prediction of Wear Morphology and Coefficient of Friction Using Acoustic Signals and Deep Neural Networks in a Tribological System. Processes. 2025; 13(6):1762. https://doi.org/10.3390/pr13061762
Chicago/Turabian StyleTian, Yang, Bohao Zheng, Muhammad Khan, and Yifan Yang. 2025. "Real-Time Prediction of Wear Morphology and Coefficient of Friction Using Acoustic Signals and Deep Neural Networks in a Tribological System" Processes 13, no. 6: 1762. https://doi.org/10.3390/pr13061762
APA StyleTian, Y., Zheng, B., Khan, M., & Yang, Y. (2025). Real-Time Prediction of Wear Morphology and Coefficient of Friction Using Acoustic Signals and Deep Neural Networks in a Tribological System. Processes, 13(6), 1762. https://doi.org/10.3390/pr13061762