A hydrogenerator model-based failure detection framework to support asset management. - Olivier Blancke; Antoine Tahan; Dragan Komljenovic; Normand Amyot; Claude Hudon; Mélanie Lévesque (ICPHM, 2016)

A holistic multi-failure mode prognosis approach for complex equipment. - Olivier Blancke; Antoine Tahan; Dragan Komljenovic; Normand Amyot; Mélanie Lévesque; Claude Hudon (Reliab. Eng. Syst. Saf., 2018)

Deep Convolutional Variational Autoencoder as a 2D-Visualization Tool for Partial Discharge Source Classification in Hydrogenerators. - Ryad A. Zemouri; Mélanie Lévesque; Normand Amyot; Claude Hudon; Olivier Kokoko; Souheil-Antoine Tahan (IEEE Access, 2020)

Comparison of an Automatic Classification of Partial Dischage Patterns for Large Hydrogenerator. - Olivier Kokoko; Claude Hudon; Mélanie Lévesque; Normand Amyot; Ryad A. Zemouri (ICPHM, 2021)

Fault detection and diagnostics in the context of sparse multimodal data and expert knowledge assistance: Application to hydrogenerators. - Sagar Jose; Khanh T. P. Nguyen; Kamal Medjaher; Ryad Zemouri; Mélanie Lévesque; Antoine Tahan (Comput. Ind., 2023)

Bridging expert knowledge and sensor measurements for machine fault quantification with large language models. - Sagar Jose; Khanh T. P. Nguyen; Kamal Medjaher; Ryad Zemouri; Mélanie Lévesque; Antoine Tahan (AIM, 2024)

Advancing multimodal diagnostics: Integrating industrial textual data and domain knowledge with large language models. - Sagar Jose; Khanh T. P. Nguyen; Kamal Medjaher; Ryad Zemouri; Mélanie Lévesque; Antoine Tahan (Expert Syst. Appl., 2024)

Prognostics of complex machinery with sparse multilabel multimodal run-to-failure data: A graph neural network approach. - Sagar Jose; Ryad Zemouri; Khanh T. P. Nguyen; Kamal Medjaher; Mélanie Lévesque; Antoine Tahan (Adv. Eng. Informatics, 2025)