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Use of predictive maintenance for onshore / offshore wind turbines

In cooperation and with the support of Wirtschaftsförderung und Technologietransfer Schleswig-Holstein GmbH, WTSHfor short, Deutsche Windtechnik's software development department at the Ostenfeld location is working on a project called Predictive Maintenance Wind Turbine.

It involves the use of machine learning, a sub-area of artificial intelligence (AI), to enable predictive maintenance for wind turbines. For this purpose, a process innovation (software) is being developed for early detection and diagnosis of faults in wind turbines to enable predictive maintenance.

The objectives of this project include:
  • Requirement-driven maintenance of wind turbines
  • Reduction of downtime for wind turbines (increased availability)
  • Increased wind turbine safety
  • Extension of the service life of the wind turbines
  • Increased quality of service and customer satisfaction
  • Expanded range of services
  • Prevention of frequent maintenance work (resource conservation)
  • Development / modification of spare parts based on knowledge gained about the events that led to the damage
  • More consistent availability and predictability of wind power for the power grid (keyword: energy transition)
     

The solution being developed will provide recommendations for action and identify the components that need to be checked during service work and brought along, if necessary. The benefits include improvements in the profitability and performance of the wind turbines, optimal points in time for maintenance work and optimised purchasing and storage of components. The project also takes into account the wind energy industry's requirement for data-driven system analysis.

The unique feature of this approach is that no additional sensors need to be installed on the system, which means that there are no costs for the operator.

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