Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy

Xie, Lubing; Rui, Xiaoming; Li, Shuai; Hu, Xin

doi:10.3390/en12142650

Cited by 21 publications

(6 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By grouping maintenance activities of different component, the maintenance cost can be minimized. Xie et al [44] developed an effective opportunistic maintenance strategy to reduce the maintenance costs of offshore wind turbines in consideration of their accessibility. Atashgar and Abdollahzadeh [3] formulated a joint redundancy and imperfect block opportunistic maintenance optimization model for wind farms, and minimizing maintenance costs is one of the objectives of the proposed model.…”

Section: Comparison Analysismentioning

confidence: 99%

An opportunistic maintenance strategy for offshore wind turbine system considering optimal maintenance intervals of subsystems

Wang²,

Kang

et al. 2020

Ocean Engineering

View full text Add to dashboard Cite

Section: Comparison Analysismentioning

confidence: 99%

An opportunistic maintenance strategy for offshore wind turbine system considering optimal maintenance intervals of subsystems

Wang²,

Kang

et al. 2020

Ocean Engineering

View full text Add to dashboard Cite

“…The findings show the effect that different maintenance costs have on the economic benefits of an opportunistic maintenance strategy. Xie et al [26] established an efficient strategy in view of accessibility for offshore wind turbines to decrease maintenance costs. A failure rate based on minimal data has been estimated using the Weibull distribution with a three-parameter process approach.…”

Section: Literature Reviewmentioning

confidence: 99%

Reliability-Based Preventive Maintenance Strategy of Truck Unloading Systems

Mohammed¹,

Ghaithan²,

Al-Saleh³

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

The unloading of petroleum products is a complex and potentially dangerous operation since the unloading system contains complex interdependency components. Any failures in one of its components lead to a cut in the petroleum supply chain. Therefore, it is important to assess and evaluate the reliability of the unloading system in order to improve its availability. In this context, this paper presents the operation philosophy of the truck unloading system, failure modes of the components within the system, and a bottom-up approach to analyze the reliability of the system. In addition, it provides reliability data, such as failure rates, and mean time between failures of the system components. Furthermore, the reliability of the whole system was calculated and is presented for different time periods. The critical components, which are major contributors towards the system reliability, were identified. To enhance the system reliability, a reliability-based preventive maintenance strategy for the critical components was implemented. In addition, the preventive maintenance scheduling was identified based on the reliability plots of the unloading system. The best schedule for preventive maintenance of the system was determined based on the reliability function to be every 45 days for maintaining the system reliability above 0.9. Findings reveal that the reliability of the unloading system was significantly improved. For instance, the system reliability at one year improved by 80%, and this ratio increased dramatically as the time period increased.

show abstract

“…In the aspect of TBM, Xie et al 28 developed the system degradation model based on the three-parameter Weibull distribution. The outcomes demonstrated that the failure rate short-term prediction of the three-parameter Weibull model was superior to the two-parameter Weibull model when the fault data were limited, improving the cost savings to 10%.…”

Section: Case Studymentioning

confidence: 99%

Condition-based maintenance for the offshore wind turbine based on long short-term memory network

Sun

Kang

Sun

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

View full text Add to dashboard Cite

This paper introduces a condition-based maintenance method combined with long short-term memory network for offshore wind turbine. According to the ranking of offshore wind turbine components using multiple indicators (failure rate, repair time, and maintenance cost), the optimization object focuses on four critical components, namely, rotor, pitch system, gearbox, and generator. Long short-term memory network is implemented to evaluate system condition and predict potential risks, then the preventive maintenance can be performed on the component that reaches the reliability threshold. The repair activity provides an advance maintenance opportunity for the other components, sharing the fix maintenance costs and the downtime. A maintenance decision process is presented in this paper, aiming to achieve the maximum cost savings. Calculated and comparative results demonstrate that the policy proposed in this article is superior in validity and accuracy.

show abstract

Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy

Cited by 21 publications

References 17 publications

An opportunistic maintenance strategy for offshore wind turbine system considering optimal maintenance intervals of subsystems

An opportunistic maintenance strategy for offshore wind turbine system considering optimal maintenance intervals of subsystems

Reliability-Based Preventive Maintenance Strategy of Truck Unloading Systems

Condition-based maintenance for the offshore wind turbine based on long short-term memory network

Contact Info

Product

Resources

About