Data-driven prognostic method based on self-supervised learning approaches for fault detection
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DOI: 10.1007/s10845-018-1431-x
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References listed on IDEAS
- A. Mosallam & K. Medjaher & N. Zerhouni, 2016. "Data-driven prognostic method based on Bayesian approaches for direct remaining useful life prediction," Journal of Intelligent Manufacturing, Springer, vol. 27(5), pages 1037-1048, October.
- Ridha Ziani & Ahmed Felkaoui & Rabah Zegadi, 2017. "Bearing fault diagnosis using multiclass support vector machines with binary particle swarm optimization and regularized Fisher’s criterion," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 405-417, February.
- Pedro Santos & Jesús Maudes & Andres Bustillo, 2018. "Identifying maximum imbalance in datasets for fault diagnosis of gearboxes," Journal of Intelligent Manufacturing, Springer, vol. 29(2), pages 333-351, February.
- Mario A. Saucedo-Espinosa & Hugo Jair Escalante & Arturo Berrones, 2017. "Detection of defective embedded bearings by sound analysis: a machine learning approach," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 489-500, February.
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Cited by:
- Abdellatif Elmouatamid & Brian Fricke & Jian Sun & Philip W. T. Pong, 2023. "Air Conditioning Systems Fault Detection and Diagnosis-Based Sensing and Data-Driven Approaches," Energies, MDPI, vol. 16(12), pages 1-20, June.
- Youngju Kim & Hoyeop Lee & Chang Ouk Kim, 2023. "A variational autoencoder for a semiconductor fault detection model robust to process drift due to incomplete maintenance," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 529-540, February.
- Ding, Yifei & Zhuang, Jichao & Ding, Peng & Jia, Minping, 2022. "Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
- Lu-jun Cui & Man-ying Sun & Yan-long Cao & Qi-jian Zhao & Wen-han Zeng & Shi-rui Guo, 2021. "A novel tolerance geometric method based on machine learning," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 799-821, March.
- Mohammed Majid Abdulrazzaq & Nehad T. A. Ramaha & Alaa Ali Hameed & Mohammad Salman & Dong Keon Yon & Norma Latif Fitriyani & Muhammad Syafrudin & Seung Won Lee, 2024. "Consequential Advancements of Self-Supervised Learning (SSL) in Deep Learning Contexts," Mathematics, MDPI, vol. 12(5), pages 1-42, March.
- Jinhai Chen & Wenyuan Zhang & Heng Wang, 2021. "Intelligent bearing structure and temperature field analysis based on finite element simulation for sustainable and green manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 745-756, March.
- Chia-Yen Lee & Chen-Fu Chien, 2022. "Pitfalls and protocols of data science in manufacturing practice," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1189-1207, June.
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Keywords
Fault detection; Self-supervised; Kernel PCA; Prognostics and health management;All these keywords.
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