Semi-Supervised Temporal Meta-Learning Framework for Wind Turbine Bearing Fault Diagnosis Under Limited Annotation Data.
Hao SuQingtao YaoLing XiangAijun HuPublished in: IEEE Trans. Instrum. Meas. (2024)
Keyphrases
- fault diagnosis
- semi supervised
- meta learning
- data sets
- expert systems
- knowledge discovery
- fault detection
- monitoring and fault diagnosis
- labeled data
- neural network
- wind turbine
- data analysis
- historical data
- power system
- machine learning algorithms
- test data
- supervised learning
- data points
- fault identification
- case study