Bearing Fault Diagnosis of Wind Motor Based on Shared-FedAvg with Non-IID Data
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-4578-6_6
Reference14 articles.
1. Changzheng C, Changcheng S, Yu Z, Nan W (2005) Fault diagnosis for large-scale wind turbine rolling bearing using stress wave and wavelet analysis [J]. In: 2005 international conference on electrical machines and systems, vol 3, pp 2239–2244
2. Cerrada M, Sanchez RV, Li C, et al (2018) A review on data-driven fault severity assessment in rolling bearings [J]. Mech Syst Signal Process 99(jan.15):169–196
3. Canizo M, Onieva E, Conde A, Charramendieta S, Trujillo S (2017) Real-time predictive maintenance for wind turbines using Big Data frameworks. In: IEEE international conference on prognostics and health management (ICPHM) 2017, pp 70–77
4. Yang Q, Liu Y, Chen T et al (2019) Federated machine learning: concept and applications [J]. ACM Trans Intell Syst Technol 10(2):1–19
5. Siddique F, Sakib S, Siddique M (2020) Recognition of handwritten digit using convolutional neural network in Python with Tensorflow and comparison of performance for various hidden layers [J]. In: 2019 5th international conference on advances in electrical engineering (ICAEE)
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