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Part 1: Document Description
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Citation |
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Title: |
CWRU Domain Generalization Version |
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Identification Number: |
doi:10.21979/N9/8QPQHL |
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Distributor: |
DR-NTU (Data) |
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Date of Distribution: |
2023-04-03 |
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Version: |
1 |
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Bibliographic Citation: |
Ragab, Mohamed, 2023, "CWRU Domain Generalization Version", https://doi.org/10.21979/N9/8QPQHL, DR-NTU (Data), V1 |
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Citation |
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Title: |
CWRU Domain Generalization Version |
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Identification Number: |
doi:10.21979/N9/8QPQHL |
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Authoring Entity: |
Ragab, Mohamed (Nanyang Technological University) |
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Software used in Production: |
Python |
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Grant Number: |
AME Programmatic Funds (Grant No. A20H6b0151) |
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Grant Number: |
Career Development Award (Grant No. C210112046) |
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Distributor: |
DR-NTU (Data) |
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Access Authority: |
Ragab, Mohamed |
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Depositor: |
Ragab, Mohamed |
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Date of Deposit: |
2022-03-06 |
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Holdings Information: |
https://doi.org/10.21979/N9/8QPQHL |
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Study Scope |
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Keywords: |
Engineering, Engineering, Domain Generalization, Fault Diagnosis |
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Abstract: |
The Case Western Reserve University (CWRU) is a widely adopted dataset for rolling bearing elements (Smith and Randall 2015). Accelerometer sensors were deployed at both the drive-end and fan-end of the housing motors. Vibration signals were collected with 12 KHz sampling rate under eight different operating conditions. Particularly, we have four different operating conditions with different loading torques collected from the drive end, denoted as domain A, B, C, and D. Similarly, we have other four operating conditions collected from the fan-end of the motor, denoted as domain F, G, H, and I. For each operating condition, there is one healthy state and three faulty states, namely, inner fault (IF), outer fault (OF), and bearing fault (BF). Each faulty state has three levels of severity with dimensions of 7, 14, 21 mil. In total, we have 10 classes with 1 healthy class and 9 faulty classes. To prepare the data for our experiments, we partitioned the sensor readings into smaller samples using sliding windows with a fixed length of 4,096 and the shifting step of 290, which is widely used in previous studies (Zhang et al. 2017; Ragab et al. 2021). Overall, we can generate 4,000 samples for each domain. |
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Kind of Data: |
Time series |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Identification Number: |
10.1109/TIM.2022.3154000 |
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Bibliographic Citation: |
Ragab, M., Chen, Z., Zhang, W., Eldele, E., Wu, M., Kwoh, C. K., & Li, X. (2022). Conditional Contrastive Domain Generalization for Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement, 71, 3506912-. |
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Citation |
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Identification Number: |
10356/163780 |
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Bibliographic Citation: |
Ragab, M., Chen, Z., Zhang, W., Eldele, E., Wu, M., Kwoh, C. K. & Li, X. (2022). Conditional contrastive domain generalization for fault diagnosis. IEEE Transactions On Instrumentation and Measurement, 71, 3506912-. |
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application/octet-stream |
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B.pt |
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application/octet-stream |
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C.pt |
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application/octet-stream |
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dg_settings_prerocessing.ipynb |
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application/x-ipynb+json |
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D.pt |
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application/octet-stream |
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E.pt |
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application/octet-stream |
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F.pt |
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application/octet-stream |
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G.pt |
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application/octet-stream |
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H.pt |
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Notes: |
application/octet-stream |