Identification of temporal anomalies of spectrograms of vibration measurements of a turbine generator rotor using a recurrent neural network autoencoder
A method is proposed for recognizing pre-emergency conditions of rotary installations based on the use of the Hamming window and advanced Deep Learning techniques in retrospective analysis of the results of accounting for the factors of operation of a turbine generator, diagnostics and control under...
Saved in:
| Main Authors: | V. P. Kulagin, D. A. Akimov, S. A. Pavelyev, E. O. Guryanova |
|---|---|
| Format: | Article |
| Language: | Russian |
| Published: |
MIREA - Russian Technological University
2021-04-01
|
| Series: | Российский технологический журнал |
| Subjects: | |
| Online Access: | https://www.rtj-mirea.ru/jour/article/view/305 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Fault Detection Framework for Rotating Machinery with a Spectrogram and Convolutional Autoencoder
by: Hoyeon Lee, et al.
Published: (2025-07-01) -
Applications of Online Condition Monitoring System and Fault Diagnosis to Wind Turbines
by: LU Shengwen, et al.
Published: (2013-01-01) -
Fuzzy Control Strategy for Wind Turbine Vibration Suppression under Complicated Operating Conditions
by: JIANG Tao, et al.
Published: (2024-04-01) -
A State-of-the-Art Review of Wind Turbine Blades: Principles, Flow-Induced Vibrations, Failure, Maintenance, and Vibration Suppression Techniques
by: Tahir Muhammad Naqash, et al.
Published: (2025-06-01) -
Detection of Abnormal Symptoms Using Acoustic-Spectrogram-Based Deep Learning
by: Seong-Yoon Kim, et al.
Published: (2025-04-01)