Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence Pattern
The chaotic squeak and rattle (S&R) vibrations in mechanical systems were classified by deep learning. The rattle, single-mode, and multi-mode squeak models were constructed to generate chaotic S&R signals. The repetition of nonlinear signals generated by them was visualized using an unthres...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/23/8054 |
| _version_ | 1797507136335380480 |
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| author | Jaehyeon Nam Jaeyoung Kang |
| author_facet | Jaehyeon Nam Jaeyoung Kang |
| author_sort | Jaehyeon Nam |
| collection | DOAJ |
| description | The chaotic squeak and rattle (S&R) vibrations in mechanical systems were classified by deep learning. The rattle, single-mode, and multi-mode squeak models were constructed to generate chaotic S&R signals. The repetition of nonlinear signals generated by them was visualized using an unthresholded recurrence plot and learned using a convolutional neural network (CNN). The results showed that even if the signal of the S&R model is chaos, it could be classified. The accuracy of the classification was verified by calculating the Lyapunov exponent of the vibration signal. The numerical experiment confirmed that the CNN classification using nonlinear vibration images as the proposed procedure has more than 90% accuracy. The chaotic status and each model can be classified into six classes. |
| first_indexed | 2024-03-10T04:44:19Z |
| format | Article |
| id | doaj.art-53b6ab4cc09f4674a7f480c3be731c15 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T04:44:19Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-53b6ab4cc09f4674a7f480c3be731c152023-11-23T03:03:15ZengMDPI AGSensors1424-82202021-12-012123805410.3390/s21238054Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence PatternJaehyeon Nam0Jaeyoung Kang1Future Automotive Intelligent Electronics Core Technology Center, Kongju National University, Cheonan 31080, KoreaDepartment of Mechanical Engineering, Inha University, Incheon 22212, KoreaThe chaotic squeak and rattle (S&R) vibrations in mechanical systems were classified by deep learning. The rattle, single-mode, and multi-mode squeak models were constructed to generate chaotic S&R signals. The repetition of nonlinear signals generated by them was visualized using an unthresholded recurrence plot and learned using a convolutional neural network (CNN). The results showed that even if the signal of the S&R model is chaos, it could be classified. The accuracy of the classification was verified by calculating the Lyapunov exponent of the vibration signal. The numerical experiment confirmed that the CNN classification using nonlinear vibration images as the proposed procedure has more than 90% accuracy. The chaotic status and each model can be classified into six classes.https://www.mdpi.com/1424-8220/21/23/8054squeakrattleconvolutional neural networkLyapunov exponentchaosrecurrence patterns |
| spellingShingle | Jaehyeon Nam Jaeyoung Kang Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence Pattern Sensors squeak rattle convolutional neural network Lyapunov exponent chaos recurrence patterns |
| title | Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence Pattern |
| title_full | Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence Pattern |
| title_fullStr | Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence Pattern |
| title_full_unstemmed | Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence Pattern |
| title_short | Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence Pattern |
| title_sort | classification of chaotic squeak and rattle vibrations by cnn using recurrence pattern |
| topic | squeak rattle convolutional neural network Lyapunov exponent chaos recurrence patterns |
| url | https://www.mdpi.com/1424-8220/21/23/8054 |
| work_keys_str_mv | AT jaehyeonnam classificationofchaoticsqueakandrattlevibrationsbycnnusingrecurrencepattern AT jaeyoungkang classificationofchaoticsqueakandrattlevibrationsbycnnusingrecurrencepattern |