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Assessment of Early Stopping through Statistical Health Prognostic Models for Empirical RUL Estimation in Wind Turbine Main Bearing Failure Monitoring.

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Title: Assessment of Early Stopping through Statistical Health Prognostic Models for Empirical RUL Estimation in Wind Turbine Main Bearing Failure Monitoring.
Authors: Herp, Jürgen1 (AUTHOR) herp@mmmi.sdu.dk, Pedersen, Niels L.2 (AUTHOR), Nadimi, Esmaeil S.1 (AUTHOR)
Source: Energies (19961073). Jan2020, Vol. 13 Issue 1, p83-83. 1p. 2 Diagrams, 1 Chart, 9 Graphs.
Database: Academic Search Ultimate
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  Data: Assessment of Early Stopping through Statistical Health Prognostic Models for Empirical RUL Estimation in Wind Turbine Main Bearing Failure Monitoring.
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Jan2020, Vol. 13 Issue 1, p83-83. 1p. 2 Diagrams, 1 Chart, 9 Graphs.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=141387259
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      – Type: doi
        Value: 10.3390/en13010083
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: 83
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      – TitleFull: Assessment of Early Stopping through Statistical Health Prognostic Models for Empirical RUL Estimation in Wind Turbine Main Bearing Failure Monitoring.
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            NameFull: Herp, Jürgen
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            NameFull: Pedersen, Niels L.
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            NameFull: Nadimi, Esmaeil S.
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              Text: Jan2020
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              Y: 2020
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              Value: 13
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