scholar.google.com › citations
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) ...
Feb 19, 2024 ， (7), which employ a convolutional layer with a 1 ／ 1 kernel size to facilitate this transition. Finally, applying the ReLU activation ...
Sep 27, 2019 ， ... Study on vibration effects of high-speed train operation on viaduct and subgrade-viaduct transition sections in loess area. Article. Jul 2024 ...
After procuring the degradation signals, we obtain DIs incorporating sufficient deterioration information using Markov Transition Fields. Next, these DIs ...
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 ...
May 5, 2023 ， Convolutional model with a time series feature based on RSSI analysis with the Markov transition field for enhancement of location recognition.
Aug 15, 2024 ， ... based on deep learning ... STO-CVAE: state transition-oriented conditional variational autoencoder for data augmentation in disability ...
Sep 4, 2023 ， It provides a smooth transition from 0 to 1, which can be useful in tasks requiring probabilistic outputs. The hyperbolic tangent function ...