A Workflow for Synthetic Data Generation and Predictive Maintenance for Vibration Data
Abstract
:1. Introduction
- A method for building a digital twin model (of a motor and gearbox circuit specifically in this study) and generating synthetic healthy and faulty data using this model is proposed.
- A predictive maintenance algorithm to estimate the current state of the machine/digital twin is presented for all types of periodic signal (vibration data specifically in this study), and steps of this algorithm are described in detail to ensure reproducibility. The proposed predictive maintenance algorithm can work with both synthetic data and suitable real-life data.
- A publicly accessible vibration dataset and digital twin model-generated synthetic data were used to test the classification accuracy of the proposed predictive maintenance algorithm, in terms of correctly classifying healthy and faulty data.
2. Methodology
2.1. Creating the Digital Twin Model
2.2. Predictive Maintenance Workflow
Algorithm 1 Synthetic Data Generation Algorithm |
Input: Description of the List of Failures |
(1) Develop Detailed Physics-Based Model of the Process |
(2) Develop and Implement Modelling Strategies of the Failures |
(3) Input Realistic Range of Variables Responsible of the Failures |
Randomly vary the Variables Responsible of the Failures |
Run Until Enough Data |
Output: Supervised Dataset for Predictive Maintenance |
2.3. Testing the Predictive Maintenance Algorithm
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Selçuk, Ş.Y.; Ünal, P.; Albayrak, Ö.; Jomâa, M. A Workflow for Synthetic Data Generation and Predictive Maintenance for Vibration Data. Information 2021, 12, 386. https://doi.org/10.3390/info12100386
Selçuk ŞY, Ünal P, Albayrak Ö, Jomâa M. A Workflow for Synthetic Data Generation and Predictive Maintenance for Vibration Data. Information. 2021; 12(10):386. https://doi.org/10.3390/info12100386
Chicago/Turabian StyleSelçuk, Şahan Yoruç, Perin Ünal, Özlem Albayrak, and Moez Jomâa. 2021. "A Workflow for Synthetic Data Generation and Predictive Maintenance for Vibration Data" Information 12, no. 10: 386. https://doi.org/10.3390/info12100386
APA StyleSelçuk, Ş. Y., Ünal, P., Albayrak, Ö., & Jomâa, M. (2021). A Workflow for Synthetic Data Generation and Predictive Maintenance for Vibration Data. Information, 12(10), 386. https://doi.org/10.3390/info12100386