Fault Diagnosis of Rotating Machinery under Noisy Environment Conditions Based on a 1-D Convolutional Autoencoder and 1-D Convolutional Neural Network.
Xingchen LiuQicai ZhouJiong ZhaoHehong ShenXiaolei XiongPublished in: Sensors (2019)
Keyphrases
- rotating machinery
- fault diagnosis
- noisy environments
- convolutional neural network
- fault detection
- operating conditions
- neural network
- expert systems
- noise reduction
- face detection
- bp neural network
- gas turbine
- restricted boltzmann machine
- speech recognition
- speech signal
- fuzzy logic
- power transformers
- multiple faults
- condition monitoring
- fault detection and diagnosis
- rbf neural network
- electronic equipment
- chemical process
- multi sensor information fusion
- power plant
- artificial intelligence
- analog circuits
- data fusion
- detection method
- multiresolution
- information retrieval
- monitoring and fault diagnosis
- machine learning