Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data

• Published in: IEEE transactions on industrial electronics (1982) Vol. 66; no. 9; pp. 7316 - 7325
• Main Authors: Guo, Liang, Lei, Yaguo, Xing, Saibo, Yan, Tao, Li, Naipeng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation; Artificial neural networks; Bearing; Convolution; convolutional neural network (CNN); Data acquisition; Fault diagnosis; Feature extraction; Feature recognition; intelligent fault diagnosis; Learning; Learning systems; Modules; Probability distribution; Testing; Training; transfer learning

The success of intelligent fault diagnosis of machines relies on the following two conditions: 1) labeled data with fault information are available; and 2) the training and testing data are drawn from the same probability distribution. However, for some machines, it is difficult to obtain massive la...