A stochastic model of preventive maintenance strategies for wind turbine gearboxes considering the incomplete maintenance.

Journal

Scientific reports

ISSN: 2045-2322

Titre abrégé: Sci Rep

Pays: England

ID NLM: 101563288

Informations de publication

Date de publication:
08 Mar 2024

Historique:

received: 13 09 2023

accepted: 06 03 2024

medline: 9 3 2024

pubmed: 9 3 2024

entrez: 8 3 2024

Statut: epublish

Résumé

In contemporary large wind farms, the combination of condition-based maintenance (CBM) and time-based maintenance (TBM) has become a prevalent approach in preventive maintenance, which is an indispensable part to ensure the safe, stable and environmental operation of equipment. However, the utilization of an inappropriate maintenance strategy may result in over-maintenance or under-maintenance, leading to unstable equipment operation. Furthermore, the majority of preventive maintenance involves replacement maintenance, which may have adverse effects on the performance of wind turbines with excessive maintenance time. Therefore, this paper takes the gearbox as a case study to introduce the incomplete maintenance parameters into the failure rate function to establish a state model based on the stochastic differential equation (SDE) and describing the state change of incomplete maintenance. And then simulating the state model of the gearbox and the joint preventive maintenance strategy of TBM and CBM through examples, resulting the time-based incomplete maintenance (TBIM) is proposed based on the TBM and the incomplete maintenance, and a new joint preventive maintenance strategy incorporating TBIM and CBM is proposed. Through developing the decision-making process of the maintenance strategy to optimize the inappropriate maintenance which including over-maintenance and under-maintenance and simulating the optimized preventive maintenance strategy to compare with that of TBM and CBM and verify the superiority and effectiveness of the proposed maintenance method.

Identifiants

DOI: 10.1038/s41598-024-56436-0 PMID: 38459121

pubmed: 38459121

doi: 10.1038/s41598-024-56436-0

pii: 10.1038/s41598-024-56436-0

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

5700

Subventions

Organisme : National Natural Science Foundation of China

ID : 6186 7003

Informations de copyright

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