Aug 2026· Nondestructive Testing and Evaluation· Vol 41, pp. 4470 - 4499· 4 citations· 48 references
TL;DR
Experimental results show that the proposed dynamic wavelet optimisation and hierarchical reinforcement learning method outperforms state-of-the-art methods in both performance and reliability.
Remaining useful life prediction for rotating machinery under non-stationary operating conditions demands effective extraction of degradation features from multi-sensor signals with varying spectral characteristics. This study proposes a WKCL-MBiTCN-Modified Informer hybrid framework that integrates a wavelet kernel co...
Dong Yang, Jun Shao, Cun Yang et al.· Engineering Research Express· 0 citations
To address diagnostic challenges in feature extraction and parameter tuning for wind turbine gearboxes, this study proposes a diagnostic model that integrates the Gramian angular field, a convolutional neural network, and a least-squares support vector machine optimized by the dream optimization algorithm. First, Grami...
Zhi-Hao Fan, Mi-Nan Tang, Han-Ting Li et al.· Transactions of the Institut...· 0 citations
To address distribution shift and degraded generalization in rolling bearing fault diagnosis under varying operating conditions, such as fluctuating speeds and loads, this paper proposes a hybrid diagnostic framework termed wavelet packet decomposition-one-dimensional convolutional neural network-spiking neural network...
A novel hybrid intelligent framework—integrating Improved Lotus Effect Algorithm, Variational Mode Decomposition, and ensemble deep learning—specifically designed for ultra-short-term wind power prediction in energy dispatch applications is engineers, which employs elite chaotic opposition-based learning to autonomousl...
Lei Shen, Qifeng Xiang, Q. Gao et al.· Energy Engineering· 0 citations
As wind turbines evolve toward larger capacities, fleet-level clustering, and operation under complex conditions, fault mechanisms in key drivetrain components show multi-physics coupling and complex evolution, creating a major bottleneck in condition monitoring: models are often constructible but hard to generalize. A...
Xue-Yi Li, Zi-Ge Wang, Wen-Yang Hu et al.· Intelligence & Robotics· 0 citations
