A hybrid methodology for classifying degradation stages and estimating a relative RUL-related degradation indicator for bearings is proposed by integrating synthetic data modeling, feature selection, and a combined unsupervised–supervised learning approach, offering a reliable and scalable solution for predictive maint...
Gustavo Gomes Do Valle, Benjamin Soudhan, Meisam Mahdavi et al.· IEEE Access· 0 citations
This study proposes an integrated condition-monitoring and predictive-maintenance framework for offshore wind turbines operating in harsh marine environments. To address the challenges of signal degradation, environmental interference, and limited fault-warning capability, a multi-source sensing architecture is develop...
Yanqing Ouyang, W. Liang· Advanced Electromagnetics· 0 citations
Hydromachinery is vital for clean and sustainable power generation, where reliable and efficient operation directly supports the stability of hydropower plants. To achieve this, real-time performance tracking and fault monitoring are becoming increasingly important. This review summarizes recent techniques and technolo...
Juhi Padma, Hemant J. Sagar· IOP Conference Series: Earth...· 0 citations
Results show that using statistical vibration features with ensemble classifiers is a good way to diagnose multi-class bearing faults and establishes a comprehensive benchmark for ML- and DL-based rolling bearing FDD.
M. I. Quamar, Abdulrazaq Nafiu Abubakar, Ali Nasir· Journal of Vibration Enginee...· 0 citations
In practical applications of rolling bearings, variations in the measurement data distribution caused by diverse operating conditions result in complicated domain adaptation tasks and significantly impair the effectiveness and generalizability of conventional models. Therefore, this study proposes a frequency-domain-aw...
Shu-Hao Wang, Peng Shen, Ming-Kai Wang et al.· Engineering Research Express· 0 citations
Aiming at the precise diagnosis requirements for multiple types of rolling bearing faults and reducing the impact of bearing faults on the operational performance of mechanical equipment, an intelligent fault diagnosis method combining wavelet packet transform (WPT) energy feature extraction and AdaBoost.M2 is proposed...
Xiao-Xuan Jiao, Xin Tao, Wen-Bo Zhang et al.· 2026 8th International Confe...· 0 citations
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