Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Minan Tang

View on Semantic Scholar

3 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Sep 2026

Vibration signal transformation-based fault diagnosis for wind turbine gearboxes considering deep feature optimization

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. · 0 citations
Jul 2026

Adaptive variational mode decomposition with attention-guided deep learning for multi-source fault diagnosis of wind turbine rotor imbalance

A hybrid diagnostic framework integrating the Ivy algorithm-optimized variational mode decomposition with an attention-enhanced temporal convolutional network and support vector machine classifier is proposed, confirming the framework’s high accuracy and generalization capability for multi-source rotor imbalance identi...

Mi-Nan Tang, Yue Pan, Yu-Ao Wu et al. · 0 citations
Aug 2026

Fault diagnosis of wind turbine gearboxes using SABO-optimised VMD and CNN-SVM integrated model

A gearbox fault diagnosis method that integrates variational mode decomposition optimised by the subtraction-average-based optimiser (SABO) with a classification framework combining convolutional neural network (CNN) and support vector machine (SVM), which achieves a diagnostic accuracy of 96.43%, significantly outperf...

Minan Tang, Zhi-Hao Fan, Jinping Li et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.