Classification of sympathetic skin response based on the morphologic features and Adaptive Neuro Fuzzy Inference system( ANFIS)

Autor: nourhene dhouibi, Jaouher BEN ALI, Mounir SAYADI, Jacques GRAPPERON, Jean-Marc GINOUX

The prevalence of polyneuropathy (PNP) or peripheral neuropathy (PN) is estimated to be 2%-3% in the general population and may be as high as 8% in people over 55 years of age. It’s the most common type of disorder of the peripheral nervous system

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8d2984b46946cc5aba470b504400daf2
https://doi.org/10.21203/rs.3.rs-2957332/v1

Particle Filter Based Approach for Remaining Useful Life Prediction of High-Speed Shaft Bearing in Wind Turbine Generators

Autor: Sharaf Eddine Kramti, Jaouher Ben Ali, Hugo Andre, Eric Brhhoefer, Mounir Sayadi

Publikováno v: Model-Based Control Engineering-Recent Design and Implementations for Varied Applications

This work involves a novel data-driven procedure using vibration analysis for bearing health prognosis. In this work, we investigate the time-domain features and applying spectral kurtosis features in order to extract the damage indicators which even

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f8156114030c945aca9c8c8ed36c246
https://mts.intechopen.com/articles/show/title/particle-filter-based-approach-for-remaining-useful-life-prediction-of-high-speed-shaft-bearing-in-w

A neural network approach for improved bearing prognostics of wind turbine generators

Autor: Sharaf Eddine Kramti, Eric Bechhoefer, Mounir Sayadi, Jaouher Ben Ali, Moez Bouchouicha, Lotfi Saidi

Publikováno v: European Physical Journal: Applied Physics
European Physical Journal: Applied Physics, 2021, 93 (2), pp.20901. ⟨10.1051/epjap/2021200259⟩
European Physical Journal: Applied Physics, EDP Sciences, 2021, 93 (2), pp.20901. ⟨10.1051/epjap/2021200259⟩

Condition monitoring of High-Speed Shaft Bearing (HSSB) in Wind Turbine Generators (WTGs) remains a challenging subject for industrial and academic studies. The investigation of mechanical vibration signals presents the most popular method in the lit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2dee53767228c32f445df6f21fc92c83
https://hal.science/hal-03170950

Online automatic diagnosis of wind turbine bearings progressive degradations under real experimental conditions based on unsupervised machine learning

Autor: Eric Bechhoefer, Jaouher Ben Ali, Mohamed Benbouzid, Salma Harrath, Lotfi Saidi

Publikováno v: Applied Acoustics. 132:167-181

As a critical component, failures of high-speed shaft bearing in wind turbines cause the unplanned stoppage of electrical energy production. Investigations related to naturally progressed defects of high-speed shaft bearings are relatively scarce and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2ceb104f67624e86968928a86e5e5541
https://doi.org/10.1016/j.apacoust.2017.11.021

Wind turbine high-speed shaft bearings health prognosis through a spectral Kurtosis-derived indices and SVR

Autor: Jaouher Ben Ali, Mohamed Benbouzid, Eric Bechhoefer, Lotfi Saidi

Publikováno v: Applied Acoustics. 120:1-8

A significant number of failures of wind turbine drivetrains occur in the high-speed shaft bearings. In this paper, a vibration-based prognostic and health monitoring methodology for wind turbine high-speed shaft bearing (HSSB) is proposed using a sp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0250b64f660ba0b5a1923ad2579a629a
https://doi.org/10.1016/j.apacoust.2017.01.005