A systematic Failure Mode Effects and Criticality Analysis for offshore wind turbine systems towards integrated condition based maintenance strategies

Scheu, Matti Niclas; Tremps, Lorena; Smolka, Ursula; Kolios, Athanasios; Brennan, Feargal

doi:10.1016/j.oceaneng.2019.02.048

Cited by 121 publications

(46 citation statements)

References 44 publications

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“…Using HS, estimation for unforeseen engine type could be performed in a robust manner; information on engine archetype is stored in hyperparameters of layer 1 with which prediction can be made. In other words, the pre-fitted values of α 0 , w 0 , and B-spline on averaged time series data are used for α s and w s (layer 3 parameters) from Equation (1).…”

Section: New Ship With Its Engine Type Not Included In Train Setmentioning

confidence: 99%

Hierarchical spline for time series prediction: An application to naval ship engine failure rate

Moon

Choi

2021

Applied AI Letters

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Predicting equipment failure is important because it could improve availability and cut down the operating budget. Previous literature has attempted to model failure rate with bathtub-formed function, Weibull distribution, Bayesian network, or analytic hierarchy process. But these models perform well with a sufficient amount of data and could not incorporate the two salient characteristics: imbalanced category and sharing structure. Hierarchical model has the advantage of partial pooling. The proposed model is based on Bayesian hierarchical B-spline. Time series of the failure rate of 99 Republic of Korea Naval ships are modeled hierarchically, where each layer corresponds to ship engine, engine type, and engine archetype. As a result of the analysis, the suggested model predicted the failure rate of an entire lifetime accurately in multiple situational conditions, such as prior knowledge of the engine.

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Section: New Ship With Its Engine Type Not Included In Train Setmentioning

confidence: 99%

Hierarchical spline for time series prediction: An application to naval ship engine failure rate

Moon

Choi

2021

Applied AI Letters

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“…There are several failure mechanisms which are time dependent and expected to occur, such as marine growth, scour, corrosion and some others [42,43]. The model includes these at the level which they are generally expected, or an average amount over the lifetime of the structure.…”

Section: Case Study Structure and Modelmentioning

confidence: 99%

Feasibility for Damage Identification in Offshore Wind Jacket Structures through Monitoring of Global Structural Dynamics

2020

Self Cite

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The modal response of a four-legged jacket structure to damages are explored and resulting considerations for damage detection are discussed. A finite element model of the Wikinger (Iberdrola) jacket structure is used to investigate damage detection. Damages, such as cracks, scour, corrosion and more, are modelled in a simulation environment. The resulting modal parameters are calculated, these parameters are compared to those from an unaltered structure and metrics are calculated including frequency change, modal assurance criterion and modal flexibility. A highly detailed design-model is used to conduct a sensitivity study on modal parameters for a range of changes. By conducting this on the same structure, this acts as a useful reference for those interested in the dynamic response of offshore wind jacket structures. Additionally, this paper addresses the issue of changes in mode parameters resulting from turbine yaw. This paper also considers the challenge of mode-swapping in semi-symmetric structures and proposes several approaches for addressing this. Damage typically results in a reduction of frequency and change in mode shapes, but in ways which can be distinguished from other structural changes, given the extent of this model. These findings are important considerations for modal-based damage detection of offshore wind support structures.

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“…Today, strategies that are centered on risk-based assessment are acknowledged by practitioners as the most effective ones for energy asset management [7], [19], [20].…”

Section: Review Of Strategies For Energy Asset Managementmentioning

confidence: 99%

Asset Management of Energy Company Based on Risk-Oriented Strategy

Gitelman

Kozhevnikov

Chebotareva

et al. 2020

WIT Transactions on Ecology and the Environment

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Repairs and maintenance of energy assets can be carried out in a variety of ways, which are usually based on indicators of reliability and efficiency. Due to the transition to a digital energy paradigm and implementation of intelligent diagnostic tools for technical condition of the equipment, it is advisable to carry out asset management with additional tools to consider operational and economic risks, as well as to predict the integrated efficiency of energy objects. This paper presents an overview of progressive strategies for energy asset management currently used in global practice. The analysis of approaches to asset management developed by one of the largest Russian generating and grid utilities is carried out. The authors developed several methodological recommendations for the identification of priority objects for technical maintenance and repair, ranked based on the type of equipment, risk of failure, predictiveness of defects, the undersupply of energy in emergency situations, types and cost of remediation and reputation losses of the energy business. Proposals for energy companies to implement a risk-based assets management strategy in units operating energy facilities are formulated.

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A systematic Failure Mode Effects and Criticality Analysis for offshore wind turbine systems towards integrated condition based maintenance strategies

Cited by 121 publications

References 44 publications

Hierarchical spline for time series prediction: An application to naval ship engine failure rate

Hierarchical spline for time series prediction: An application to naval ship engine failure rate

Feasibility for Damage Identification in Offshore Wind Jacket Structures through Monitoring of Global Structural Dynamics

Asset Management of Energy Company Based on Risk-Oriented Strategy

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