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Remaining useful life prediction of machinery under time-varying operating conditions based on a two-factor state-space model., , , , и . Reliab. Eng. Syst. Saf., (2019)A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings., , , и . IEEE Trans. Reliab., 69 (1): 401-412 (2020)Deep multisource parallel bilinear-fusion network for remaining useful life prediction of machinery., , , , и . Reliab. Eng. Syst. Saf., (2023)Balance recovery and collaborative adaptation approach for federated fault diagnosis of inconsistent machine groups., , , , , и . Knowl. Based Syst., (2025)Self-Data-Driven Intelligent Fault Diagnosis of Gearboxes With Sparse Group Lasso., , , , , и . IEEE Trans. Instrum. Meas., (2025)Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data., , , , и . IEEE Trans. Ind. Electron., 66 (9): 7316-7325 (2019)Non-Contact Machine Vibration Sensing and Fault Diagnosis Method Based on Event Camera., , , , и . SAFEPROCESS, стр. 1-5. IEEE, (2023)Degradation modeling and remaining useful life prediction for dependent competing failure processes., , , , и . Reliab. Eng. Syst. Saf., (2021)Joint maintenance and spare parts inventory optimization for multi-unit systems considering imperfect maintenance actions., , , , , и . Reliab. Eng. Syst. Saf., (2020)Machinery Health Prognostics With Multimodel Fusion Degradation Modeling., , , , и . IEEE Trans. Ind. Electron., 70 (11): 11764-11773 (ноября 2023)