Wind Turbine Components Classification based on Failure Causes for Proactive Maintenance Simulation

Bezzaoucha, Fatima Souad; Sahnoun, M’hammed; Benslimane, Sidi Mohamed

doi:10.1109/icmsao.2019.8880370

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…This paper extends the work originally presented in Bezzaoucha et al (2019). It proposes a degradation model based on a new classification of the subsystems of an indirect drive wind turbine (turbines with gearbox) according to their failure causes to characterize the phenomenon of failure propagation.…”

Section: Introductionmentioning

confidence: 85%

Multi-component modeling and classification for failure propagation of an offshore wind turbine

Bezzaoucha

Sahnoun²,

Benslimane

2020

IJESM

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Purpose Improving reliability is a key factor in reducing the cost of wind energy, which is strongly influenced by the cost of maintenance operations. In this context, this paper aims to propose a degradation model that describes the phenomenon of fault propagation to apply proactive maintenance that will act on the cause of failure to prevent its reoccurrence as well as to improve future system designs. Design/methodology/approach The methodology adopted consists in identifying the different components of a wind turbine, their causes and failure modes, and then, classifying these components according to their causes of failure. Findings The result is a classification of the different components of a wind turbine according to their failure causes. From the obtained classification, the authors observed that the failure modes for one component are a failure cause for another component, which describes the phenomenon of failure propagation. Originality/value The different classifications existing in the literature depend on the nature, position and function of the different components. The classification of this study consists in grouping the components of a wind turbine according to their failure causes to develop a degradation model considering the propagation of failure in the field of wind turbines.

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Section: Introductionmentioning

confidence: 85%

Multi-component modeling and classification for failure propagation of an offshore wind turbine

Bezzaoucha

Sahnoun²,

Benslimane

2020

IJESM

Self Cite

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Multi-agent modeling and simulation of wind turbine behavior with failure propagation consideration

Bezzaoucha

Sahnoun²,

Benslimane

2021

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-Being (IHSH)

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System-level failure prognostics: Literature review and main challenges

Tamssaouet

Nguyen

Medjaher

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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This paper reviews methods and practices for addressing the concepts of system-level prognostics (SLP) and system remaining useful life (SRUL) estimation applied to multicomponent systems. A precise definition of SLP is provided, emphasizing the advantages of its use in terms of identifying the scope of SLP applications. In addition, a comprehensive review of the literature is provided to properly classify and compare the findings of previously published studies in the field of SLP and evaluate the effectiveness of the available methodologies within the different stages of prognostic development. Finally, and considering that SLP is still a relatively recent research field, we also provide a thorough discussion on the main challenges that remain to be solved before achieving complete technology transfer, as well as future research directions.

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Wind Turbine Components Classification based on Failure Causes for Proactive Maintenance Simulation

Cited by 3 publications

References 26 publications

Multi-component modeling and classification for failure propagation of an offshore wind turbine

Multi-component modeling and classification for failure propagation of an offshore wind turbine

Multi-agent modeling and simulation of wind turbine behavior with failure propagation consideration

System-level failure prognostics: Literature review and main challenges

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