A Support Vector Machine-Based Approach for Bolt Loosening Monitoring in Industrial Customized Vehicles
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Setup and Data Acquisition
2.2. Feature Selection
2.3. Support Vector Machines Models
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Case ID | Engaged Gear | Fault Description | Class |
---|---|---|---|
M4-G | 4th | No fault | G |
M5-G | 5th | No fault | G |
M6-G | 6th | No fault | G |
M4-F1 | 4th | Two opposite bolts are loosened | F1 |
M5-F1 | 5th | Two opposite bolts are loosened | F1 |
M6-F1 | 6th | Two opposite bolts are loosened | F1 |
M4-F2 | 4th | All four bolts are loosened | F2 |
M5-F2 | 5th | All four bolts are loosened | F2 |
M6-F2 | 6th | All four bolts are loosened | F2 |
SVM Model | Gears | Accelerometers | Dataset Size |
---|---|---|---|
A1-A2 M4 | 4th | A1 and A2 | 198 |
A1-A2 M5 | 5th | A1 and A2 | 198 |
A1-A2 M6 | 6th | A1 and A2 | 198 |
A1-A2 M4-M5-M6 | 4th-5th-6th | A1 and A2 | 594 |
A3-A4 M4 | 4th | A3 and A4 | 198 |
A3-A4 M5 | 5th | A3 and A4 | 198 |
A3-A4 M6 | 6th | A3 and A4 | 198 |
A3-A4 M4-M5-M6 | 4th-5th-6th | A3 and A4 | 594 |
A1-A2-A3-A4 M4 | 4th | A1, A2, A3 and A4 | 396 |
A1-A2-A3-A4 M5 | 5th | A1, A2, A3 and A4 | 396 |
A1-A2-A3-A4 M6 | 6th | A1, A2, A3 and A4 | 396 |
A1-A2-A3-A4 M4-M5-M6 | 4th-5th-6th | A1, A2, A3 and A4 | 1188 |
SVM Model | Test Set Size | Overall Accuracy | Overall Precision | Overall Recall | Overall F-Measure |
---|---|---|---|---|---|
A1-A2 M4 | 39 | 94.9% | 94.9% | 94.9% | 94.9% |
A1-A2 M5 | 39 | 100.0% | 100.0% | 100.0% | 100.0% |
A1-A2 M6 | 39 | 94.9% | 95.0% | 94.9% | 95.0% |
A1-A2 M4-M5-M6 | 119 | 90.7% | 90.7% | 90.7% | 90.7% |
A3-A4 M4 | 39 | 92.3% | 93.8% | 92.3% | 93.0% |
A3-A4 M5 | 39 | 79.5% | 84.6% | 79.5% | 82.0% |
A3-A4 M6 | 39 | 82.1% | 82.5% | 82.0% | 82.3% |
A3-A4 M4-M5-M6 | 119 | 89.8% | 90.0% | 89.9% | 90.0% |
A1-A2-A3-A4 M4 | 79 | 87.3% | 88.0% | 87.5% | 87.7% |
A1-A2-A3-A4 M5 | 79 | 91.1% | 91.2% | 91.2% | 91.2% |
A1-A2-A3-A4 M6 | 79 | 93.7% | 93.8% | 93.7% | 93.7% |
A1-A2-A3-A4 M4-M5-M6 | 237 | 92.4% | 92.4% | 92.4% | 92.4% |
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Carone, S.; Pappalettera, G.; Casavola, C.; De Carolis, S.; Soria, L. A Support Vector Machine-Based Approach for Bolt Loosening Monitoring in Industrial Customized Vehicles. Sensors 2023, 23, 5345. https://doi.org/10.3390/s23115345
Carone S, Pappalettera G, Casavola C, De Carolis S, Soria L. A Support Vector Machine-Based Approach for Bolt Loosening Monitoring in Industrial Customized Vehicles. Sensors. 2023; 23(11):5345. https://doi.org/10.3390/s23115345
Chicago/Turabian StyleCarone, Simone, Giovanni Pappalettera, Caterina Casavola, Simone De Carolis, and Leonardo Soria. 2023. "A Support Vector Machine-Based Approach for Bolt Loosening Monitoring in Industrial Customized Vehicles" Sensors 23, no. 11: 5345. https://doi.org/10.3390/s23115345