RESONANCE 2023

Session

13 Jul 2023, 10:40

Toulouse

Conveners

Survishino 13 / Data driven condition monitoring 2

• Wylomanska Agnieszka ()

Contribution list Timetable

203. "DATA2#1 - Detection of machine mechanical faults using vibrations and deep autoencoders"

Eltabach Mario

13/07/2023, 10:40

Deep learning models represent a new learning paradigm in artificial intelligence (AI). Recent breakthroughs in image analysis and voice recognition have generated enormous interest in many other areas such as the diagnosis of rotating machinery providing voluminous data during the life of these machines. A gear endurance test bench was designed to create a database of vibration signals...

204. "DATA2#2 - Wind turbine gearbox condition monitoring through a multi-scale data-driven approach"

Castellani Francesco

13/07/2023, 11:00

Since wind is expected to play a crucial role on the worldwide electricity production scenario, the reliability of the turbines is attracting attention from industry as well from the scientific community. New techniques for efficient condition monitoring of the key components can be fundamental in order to optimize the performance and the maintenance of a large fleet of turbines. The gearbox...

205. "DATA2#3 - Vibration-based unsupervised detection of common faults in rotating machinery under varying operating speeds"

Bourdalos Dimitrios M.

13/07/2023, 11:20

Automated condition monitoring (CM) of Rotating Machinery (RM) has several benefits for modern industry including enhanced safety and reduced maintenance costs. Vibration signals may be easily and inexpensively collected from a RM during its normal operation and include rich information about the RM dynamics the proper exploitation of which may lead to effective CM. However, RM operate...

332. DATA2#4

13/07/2023, 11:40