Research on fault diagnosis for power transformer based on random forests and wavelet transform.
Ming ZhangChongfeng FangShuang JiPublished in: Int. J. Wirel. Mob. Comput. (2024)
Keyphrases
- random forests
- power transformers
- fault diagnosis
- wavelet transform
- random forest
- multiresolution
- decision trees
- machine learning algorithms
- expert systems
- multiscale
- logistic regression
- fault detection
- ensemble methods
- subband
- condition monitoring
- bp neural network
- vibration signal
- neural network
- wavelet analysis
- fault detection and diagnosis
- gas turbine
- feature extraction
- electronic equipment
- fuzzy logic
- multiple faults
- operating conditions
- high frequency
- machine learning methods
- decision tree ensembles
- analog circuits
- multi sensor information fusion
- power plant
- learning algorithm
- data mining
- chemical process
- machine learning
- monitoring and fault diagnosis