Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information

Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To "control" this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and...

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Main Authors: Ramírez, José G. Rangel, Sørensen, John Dalsgaard
Format: Article in Journal/Newspaper
Language:English
Published: American Society of Mechanical Engineers 2009
Subjects:
Online Access:https://vbn.aau.dk/da/publications/363c6dfa-d3db-4080-aa54-e57acd7d16ad
https://vbn.aau.dk/ws/files/55336005/Maintenance_Planning_of_Offshore_Wind_Turbine_using_Condition_Monitoring_Information
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spelling ftalborgunivpubl:oai:pure.atira.dk:publications/363c6dfa-d3db-4080-aa54-e57acd7d16ad 2024-09-15T17:50:23+00:00 Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information Ramírez, José G. Rangel Sørensen, John Dalsgaard 2009 application/pdf https://vbn.aau.dk/da/publications/363c6dfa-d3db-4080-aa54-e57acd7d16ad https://vbn.aau.dk/ws/files/55336005/Maintenance_Planning_of_Offshore_Wind_Turbine_using_Condition_Monitoring_Information eng eng American Society of Mechanical Engineers https://vbn.aau.dk/da/publications/363c6dfa-d3db-4080-aa54-e57acd7d16ad urn:ISBN:9780791838440 info:eu-repo/semantics/openAccess Ramírez , J G R & Sørensen , J D 2009 , Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information . in Proceedings of the 28 th International Conference on Ocean, Offshore and Arctic Engineering : OMAE2009, May 31- June 5, 2009, Honolulu, Hawaii, USA . American Society of Mechanical Engineers , The International Conference on Ocean, Offshore and Arctic Engineering (OMAE) , Honolulu, Hawaii , United States , 31/05/2009 . Maintenance Planning Offshore Wind Turbine contributionToPeriodical 2009 ftalborgunivpubl 2024-08-06T23:52:00Z Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To "control" this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and control the deterioration in structures such as offshore wind turbines (OWT). Besides these methods, the integration of condition monitoring information (CMI) can optimize the mitigation activities as an updating tool. In this paper, a framework for risk-based inspection and maintenance planning (RBI) is applied for OWT incorporating CMI, addressing this analysis to fatigue prone details in welded steel joints at jacket or tripod steel support structures for offshore wind turbines. The increase of turbulence in wind farms is taken into account by using a code-based turbulence model. Further, additional modes t integrate CMI in the RBI approach for optimal planning of inspection and maintenance. As part of the results, the life cycle reliabilities and inspection times are calculated, showing that earlier inspections are needed at in-wind farm sites. This is expected due to the wake turbulence increasing the wind load. With the integration of CMI by means Bayesian inference, a slightly change of first inspection times are coming up, influenced by the reduction of the uncertainty and harsher or milder external agents. Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To "control" this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and control the deterioration in structures such as offshore wind turbines (OWT). Besides these methods, the integration of condition monitoring information (CMI) can optimize the mitigation activities as an updating tool. In this paper, a framework for risk-based inspection and maintenance planning (RBI) is applied for OWT ... Article in Journal/Newspaper Arctic Aalborg University's Research Portal
institution Open Polar
collection Aalborg University's Research Portal
op_collection_id ftalborgunivpubl
language English
topic Maintenance Planning
Offshore Wind Turbine
spellingShingle Maintenance Planning
Offshore Wind Turbine
Ramírez, José G. Rangel
Sørensen, John Dalsgaard
Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information
topic_facet Maintenance Planning
Offshore Wind Turbine
description Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To "control" this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and control the deterioration in structures such as offshore wind turbines (OWT). Besides these methods, the integration of condition monitoring information (CMI) can optimize the mitigation activities as an updating tool. In this paper, a framework for risk-based inspection and maintenance planning (RBI) is applied for OWT incorporating CMI, addressing this analysis to fatigue prone details in welded steel joints at jacket or tripod steel support structures for offshore wind turbines. The increase of turbulence in wind farms is taken into account by using a code-based turbulence model. Further, additional modes t integrate CMI in the RBI approach for optimal planning of inspection and maintenance. As part of the results, the life cycle reliabilities and inspection times are calculated, showing that earlier inspections are needed at in-wind farm sites. This is expected due to the wake turbulence increasing the wind load. With the integration of CMI by means Bayesian inference, a slightly change of first inspection times are coming up, influenced by the reduction of the uncertainty and harsher or milder external agents. Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To "control" this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and control the deterioration in structures such as offshore wind turbines (OWT). Besides these methods, the integration of condition monitoring information (CMI) can optimize the mitigation activities as an updating tool. In this paper, a framework for risk-based inspection and maintenance planning (RBI) is applied for OWT ...
format Article in Journal/Newspaper
author Ramírez, José G. Rangel
Sørensen, John Dalsgaard
author_facet Ramírez, José G. Rangel
Sørensen, John Dalsgaard
author_sort Ramírez, José G. Rangel
title Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information
title_short Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information
title_full Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information
title_fullStr Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information
title_full_unstemmed Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information
title_sort maintenance planning of offshore wind turbine using condition monitoring information
publisher American Society of Mechanical Engineers
publishDate 2009
url https://vbn.aau.dk/da/publications/363c6dfa-d3db-4080-aa54-e57acd7d16ad
https://vbn.aau.dk/ws/files/55336005/Maintenance_Planning_of_Offshore_Wind_Turbine_using_Condition_Monitoring_Information
genre Arctic
genre_facet Arctic
op_source Ramírez , J G R & Sørensen , J D 2009 , Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information . in Proceedings of the 28 th International Conference on Ocean, Offshore and Arctic Engineering : OMAE2009, May 31- June 5, 2009, Honolulu, Hawaii, USA . American Society of Mechanical Engineers , The International Conference on Ocean, Offshore and Arctic Engineering (OMAE) , Honolulu, Hawaii , United States , 31/05/2009 .
op_relation https://vbn.aau.dk/da/publications/363c6dfa-d3db-4080-aa54-e57acd7d16ad
urn:ISBN:9780791838440
op_rights info:eu-repo/semantics/openAccess
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