Semi-supervised fault diagnosis of wheelset bearings in high-speed trains using autocorrelation and improved flow Gaussian mixture model.
Jiayi WuYilei LiLimin JiaGuoping AnYan-Fu LiJérôme AntoniGe XinPublished in: Eng. Appl. Artif. Intell. (2024)
Keyphrases
- fault diagnosis
- gaussian mixture model
- high speed
- semi supervised
- condition monitoring
- mixture model
- neural network
- fault detection
- expert systems
- electronic equipment
- chemical process
- em algorithm
- semi supervised learning
- analog circuits
- monitoring and fault diagnosis
- multiple faults
- gas turbine
- power transformers
- bp neural network
- expectation maximization
- fault detection and diagnosis
- feature vectors
- vibration signal
- speaker identification
- operating conditions
- fuzzy logic
- background subtraction
- multi sensor information fusion
- unsupervised learning
- maximum likelihood
- active learning
- pairwise
- non stationary
- computer vision
- prior knowledge
- machine learning
- artificial intelligence
- real time
- similarity measure
- multiscale
- probabilistic model
- k means
- fault diagnostic
- reinforcement learning