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Traditional fault-diagnosis methods, such as state-sensitive and transition ... Vibration analysis is an important diagnostic tool in industrial data analysis ...
Motor Fault Diagnosis and Detection with Convolutional Autoencoder (CAE) Based on Analysis of Electrical Energy Data ... transition. 2.1. Importance and ...
For this purpose, several signal-to-image encoding methods have been introduced, such as Gramian angular field (GAF) [13,14], Markov transition field (MTF) ...
... Transition Field (MTF) [14], among others. Pixel strength: Converting time series vibration data into pixel strength images involves normalizing the time ...
Jun 28, 2022A new bearing fault diagnosis method based on capsule network and markov transition field/gramian angular field. Sensors. 2021;21:7762. doi ...
Feb 19, 2024(7), which employ a convolutional layer with a 1 / 1 kernel size to facilitate this transition. Finally, applying the ReLU activation ...
Figure 2a shows four conditions according to the sizes and similarities of the dataset, and Figure 2b shows the transition learning model and the classifier's ...
... transition training correction network attention area link. Multiple sets of optimization functions are introduced into local network training to reduce the ...
Oct 8, 2024A new bearing fault diagnosis method based on capsule network and Markov transition field/Gramian angular field. ... using the Case Western ...
May 5, 2023Convolutional model with a time series feature based on RSSI analysis with the Markov transition field for enhancement of location recognition.