| A review on deep learning applications in prognostics and health management L Zhang, J Lin, B Liu, Z Zhang, X Yan, M Wei Ieee Access 7, 162415-162438, 2019 | 204 | 2019 |
| A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance H Shao, J Lin, L Zhang, D Galar, U Kumar Information Fusion 74, 65-76, 2021 | 180 | 2021 |
| Adaptive kernel density-based anomaly detection for nonlinear systems L Zhang, J Lin, R Karim Knowledge-Based Systems 139, 50-63, 2018 | 137 | 2018 |
| Sliding window-based fault detection from high-dimensional data streams L Zhang, J Lin, R Karim IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 (2), 289-303, 2016 | 119 | 2016 |
| Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots J Long, J Mou, L Zhang, S Zhang, C Li Journal of manufacturing systems 61, 736-745, 2021 | 107 | 2021 |
| An angle-based subspace anomaly detection approach to high-dimensional data: With an application to industrial fault detection L Zhang, J Lin, R Karim Reliability Engineering & System Safety 142, 482-497, 2015 | 63 | 2015 |
| A dynamic prescriptive maintenance model considering system aging and degradation B Liu, J Lin, L Zhang, U Kumar IEEE Access 7, 94931-94943, 2019 | 41 | 2019 |
| Maintenance analytics for railway infrastructure decision support SM Famurewa, L Zhang, M Asplund Journal of Quality in Maintenance Engineering 23 (3), 310-325, 2017 | 40 | 2017 |
| A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions L Zhang, Q Fan, J Lin, Z Zhang, X Yan, C Li Engineering applications of artificial intelligence 119, 105735, 2023 | 37 | 2023 |
| End-to-end unsupervised fault detection using a flow-based model L Zhang, J Lin, H Shao, Z Zhang, X Yan, J Long Reliability Engineering & System Safety 215, 107805, 2021 | 22 | 2021 |
| Big data analytics for fault detection and its application in maintenance L Zhang Luleå University of Technology, 2016 | 19 | 2016 |
| Big data mining in eMaintenance: An overview L Zhang, R Karim International Workshop and Congress on eMaintenance: 17/06/2014-18/06/2014 …, 2014 | 18 | 2014 |
| Compound fault diagnosis for a rolling bearing using adaptive DTCWPT with higher order spectra H Shao, J Lin, L Zhang, M Wei Quality Engineering 32 (3), 342-353, 2020 | 17 | 2020 |
| Maintenance service strategy for leased equipment: Integrating lessor-preventive maintenance and lessee-careful protection efforts B Liu, Y Wang, H Yang, A Segerstedt, L Zhang Computers & Industrial Engineering 156, 107257, 2021 | 11 | 2021 |
| An NSABC algorithm for multi-aisle AS/RS scheduling optimization X Yan, Z Zhang, Q Liu, C Lv, L Zhang, S Li Computers & Industrial Engineering 156, 107254, 2021 | 10 | 2021 |
| A dynamic maintenance strategy for prognostics and health management of degrading systems: Application in locomotive wheel-sets B Liu, J Lin, L Zhang, M Xie 2018 IEEE international conference on prognostics and health management …, 2018 | 10 | 2018 |
| Data clustering and imputing using a two-level multi-objective genetic algorithm (GA): A case study of maintenance cost data for tunnel fans YK Aldouri, H Al-Chalabi, L Zhang Cogent Engineering 5 (1), 1513304, 2018 | 8 | 2018 |
| Reconfiguration cost analysis based on petrinet for manufacturing system C Jie, L Zhang, LUO Jianqiang Journal of Software Engineering and Applications 2 (5), 361-369, 2009 | 8 | 2009 |
| Big data analytics for emaintenance: Modeling of high-dimensional data streams L Zhang Luleå tekniska universitet, 2015 | 6 | 2015 |
| An adaptive hydrologic cycle optimization algorithm for numerical optimization and data clustering X Yan, B Niu, Y Chai, Z Zhang, L Zhang International Journal of Intelligent Systems 37 (9), 6123-6151, 2022 | 3 | 2022 |
