Fault Diagnosis Based on Machine Learning for the High Frequency Link of a Grid-Tied Photovoltaic Converter for a Wide Range of Irradiance Conditions.
Yuniel León-RuizMario González-GarcíaRicardo Alvarez-SalasJuan Carlos Cuevas-TelloVictor M. CárdenasPublished in: IEEE Access (2021)
Keyphrases
- high frequency
- fault diagnosis
- machine learning
- low frequency
- operating conditions
- power plant
- neural network
- fault detection
- expert systems
- wind turbine
- fuzzy logic
- high resolution
- fault detection and diagnosis
- wavelet transform
- rbf neural network
- subband
- monitoring and fault diagnosis
- bp neural network
- gas turbine
- chemical process
- discrete wavelet transform
- condition monitoring
- fault identification
- wavelet coefficients
- multiple faults
- multi sensor information fusion
- electronic equipment
- rotating machinery
- power transformers
- high frequency components
- computational intelligence
- analog circuits
- wavelet decomposition
- decision making
- real time
- computer vision
- wavelet domain
- single phase
- power generation
- frequency band
- multiresolution