| Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects O Serradilla, E Zugasti, J Rodriguez, U Zurutuza Applied Intelligence 52 (10), 10934-10964, 2022 | 48 | 2022 |
| Interpreting remaining useful life estimations combining explainable artificial intelligence and domain knowledge in industrial machinery O Serradilla, E Zugasti, C Cernuda, A Aranburu, JR de Okariz, U Zurutuza 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2020 | 25 | 2020 |
| Adaptable and explainable predictive maintenance: Semi-supervised deep learning for anomaly detection and diagnosis in press machine data O Serradilla, E Zugasti, J Ramirez de Okariz, J Rodriguez, U Zurutuza Applied Sciences 11 (16), 7376, 2021 | 24 | 2021 |
| NullSpace and AutoRegressive damage detection: a comparative study E Zugasti, AG González, J Anduaga, MA Arregui, F Martínez Smart materials and structures 21 (8), 085010, 2012 | 18 | 2012 |
| Feature selection-Extraction methods based on PCA and mutual information to improve damage detection problem in offshore wind turbines E Zugasti, LE Mujica, J Anduaga, F Martinez Key Engineering Materials 569, 620-627, 2013 | 13 | 2013 |
| Impregnation quality diagnosis in resin transfer moulding by machine learning J Mendikute, J Plazaola, M Baskaran, E Zugasti, L Aretxabaleta, ... Composites Part B: Engineering 221, 108973, 2021 | 11 | 2021 |
| Design and validation of a methodology for wind energy structures health monitoring E Zugasti Uriguen Universitat Politècnica de Catalunya, 2014 | 11 | 2014 |
| Design and validation of a methodology for wind energy structures health monitoring E Zugasti Uriguen Universitat Politècnica de Catalunya, 2014 | 11 | 2014 |
| Implementation of a reference architecture for cyber physical systems to support condition based maintenance F Larrinaga, J Fernandez, E Zugasti, I Garitano, U Zurutuza, M Anasagasti, ... 2018 5th International Conference on Control, Decision and Information …, 2018 | 9 | 2018 |
| Contrastive explanations for a deep learning model on time-series data J Labaien, E Zugasti, X De Carlos Big Data Analytics and Knowledge Discovery: 22nd International Conference …, 2020 | 7 | 2020 |
| Null is not always empty: Monitoring the null space for field-level anomaly detection in industrial IoT environments E Zugasti, M Iturbe, I Garitano, U Zurutuza 2018 Global Internet of Things Summit (GIoTS), 1-6, 2018 | 7 | 2018 |
| A Big Data implementation of the MANTIS reference architecture for predictive maintenance F Larrinaga, J Fernandez-Anakabe, E Zugasti, I Garitano, U Zurutuza, ... Proceedings of the Institution of Mechanical Engineers, Part I: Journal of …, 2019 | 6 | 2019 |
| An Attribute Oriented Induction based Methodology for Data Driven Predictive Maintenance J Fernandez-Anakabe, EZ Uriguen, UZ Ortega arXiv preprint arXiv:1912.00662, 2019 | 5 | 2019 |
| DA-DGCEx: Ensuring validity of deep guided counterfactual explanations with distribution-aware autoencoder loss J Labaien, E Zugasti, X De Carlos arXiv preprint arXiv:2104.09062, 2021 | 4 | 2021 |
| Damage Identification in a Laboratory Offshore Wind Turbine Demonstrator A Gómez González, E Zugasti, J Anduaga Key Engineering Materials 569, 555-562, 2013 | 4 | 2013 |
| NullSpace Damage Detection Method with Different Environmental and Operational Conditions E Zugasti, J Anduaga, MA Arregui, F Martínez Proceedings of the 6th European Workshop of shm, 1368-1375, 2012 | 4 | 2012 |
| Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge O Serradilla, E Zugasti, J Ramirez de Okariz, J Rodriguez, U Zurutuza International Journal of Computer Integrated Manufacturing 35 (12), 1310-1334, 2022 | 3 | 2022 |
| Sensor Fault Identification on Laboratory Tower E Zugasti, P Arrillaga, J Anduaga, MA Arregui, F Martínez 6th European Workshop on Structural Health Monitoring, 1-8, 2012 | 2 | 2012 |
| A Comparative Assessment of Two SHM Damage Detection Methods in a Laboratory Tower E Zugasti, AG Gonzalez, J Anduaga, MA Arregui, F Martinez Advances in Science and Technology 83, 232-239, 2013 | 1 | 2013 |
| Diagnostic spatio-temporal transformer with faithful encoding J Labaien, T Idé, PY Chen, E Zugasti, X De Carlos Knowledge-Based Systems, 110639, 2023 | | 2023 |
Urko Zurutuza OrtegaMondragon Unibertsitatea - Data Analysis & Cybersecurity (ROR 00wvqgd19)Dirección de correo verificada de mondragon.edu
