A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model
Crossref DOI link: https://doi.org/10.1007/s40430-021-03136-9
Published Online: 2021-08-21
Published Print: 2021-09
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Montazeri-Gh, Morteza https://orcid.org/0000-0001-7003-903X
Nekoonam, Ali
Yazdani, Shabnam
Text and Data Mining valid from 2021-08-21
Version of Record valid from 2021-08-21
Article History
Received: 17 May 2020
Accepted: 31 July 2021
First Online: 21 August 2021
Declarations
:
: The authors declare that they have no conflict of interest.