Analysis of Gas Turbine Compressor Performance after a Major Maintenance Operation Using an Autoencoder Architecture

Autor: Martí de Castro-Cros, Manel Velasco, Cecilio Angulo

Publikováno v: Sensors, Vol 23, Iss 3, p 1236 (2023)

Machine learning algorithms and the increasing availability of data have radically changed the way how decisions are made in today’s Industry. A wide range of algorithms are being used to monitor industrial processes and predict process variables t

Externí odkaz: https://doaj.org/article/09cca9690fcc40179952560dc161bbd8

Machine-Learning-Based Condition Assessment of Gas Turbines—A Review

Autor: Martí de Castro-Cros, Manel Velasco, Cecilio Angulo

Publikováno v: Energies, Vol 14, Iss 24, p 8468 (2021)

Condition monitoring, diagnostics, and prognostics are key factors in today’s competitive industrial sector. Equipment digitalisation has increased the amount of available data throughout the industrial process, and the development of new and more

Externí odkaz: https://doaj.org/article/511f59c63a8645638d5a46bac43b95b5

Condition assessment of industrial gas turbine compressor using a drift soft sensor based in autoencoder

Autor: Cecilio Angulo, Manel Velasco, Edgar Bahilo, Martí de Castro-Cros, Stefano Rosso

Publikováno v: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Sensors
Volume 21
Issue 8
Sensors, Vol 21, Iss 2708, p 2708 (2021)
Sensors (Basel, Switzerland)

Maintenance is the process of preserving the good condition of a system to ensure its reliability and availability to perform specific operations. The way maintenance is nowadays performed in industry is changing thanks to the increasing availability

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91d275537c0da24b3610e171ac85676a
http://hdl.handle.net/2117/350686