Physics Guided Generative Learning for Domain Adaptable Data Synthesis : Progressive Fault Synthesization for Predictive Machine Maintenance-Reference-Cited by-同舟云学术

Physics Guided Generative Learning for Domain Adaptable Data Synthesis : Progressive Fault Synthesization for Predictive Machine Maintenance

Published:2023-10-25 Issue: Volume:35 Page:1-7
ISSN:
Container-title:The Third International Conference on Artificial Intelligence and Machine Learning Systems
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Author:

Bandyopadhyay Soma¹^ORCID,Datta Anish¹^ORCID,Sayyed Mudassir Ali²^ORCID,Chakravarty Tapas³^ORCID,Pal Arpan⁴^ORCID,Bhaumik Chirabrata⁵^ORCID

Affiliation:

1. Tata Consultancy Services Limited, India

2. Fraunhofer Enas, Germany

3. TATA Consultancy Services Limited, IN

4. Tata Consultancy Services, IN

5. TCS, IN

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3639856.3639885

Reference24 articles.

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2. Soma Bandyopadhyay, Anish Datta, and Arpan Pal. 2021. Hierarchical Clustering using Auto-encoded Compact Representation for Time-series Analysis. arXiv preprint arXiv:2101.03742 (2021).

3. Lucas Costa Brito, Gian Antonio Susto Jorge Nei Brito, and Marcus Antonio Viana Duarte. 2022. Fault Diagnosis using eXplainable AI: a Transfer Learning-based Approach for Rotating Machinery exploiting Augmented Synthetic Data. arXiv preprint arXiv:2210.02974 (2022).

4. Emotion Controllable Speech Synthesis Using Emotion-Unlabeled Dataset with the Assistance of Cross-Domain Speech Emotion Recognition

5. Gearbox Vibration Signal Amplitude and Frequency Modulation