LBM²

Load Based Monitoring and Maintenance - Optimization of the operation of onshore wind turbines by a load guided monitoring system utiizing torque sensors

The aim of the research project "LBM²" is the development of a low-cost and easy-to-use wind turbine (WT) monitoring system utilizing two software-based modules to optimize the operation and maintenance planning of the entire wind farm (WF).

The aim of the research project "LBM²" is the development of a low-cost and easy-to-use wind turbine (WT) monitoring system utilizing two software-based modules to optimize the operation and maintenance planning of the entire wind farm (WF).

The majority of wind turbines in Germany are operated by small and medium-sized enterprises. In the next few years subsidies for electricity produced by wind turbines will be successively reduced. In addition to more technically efficient systems, the operation of the system must therefore be made even more efficient. Competitive power generation throughout wind turbines does not only enable policy goals to be achieved like promoting renewable energy, but also strengthens small and medium-sized enterprises.

On the drive train of eight WT's of a WF, low-cost sensors are installed to measure the mechanical loads for one year. Together with data from the condition monitoring system and the SCADA data, calculation models for condition monitoring are developed, which form the first software module. The model describes the relationship between global farm sizes and the local load of individual components. Abrasions are determined and remaining lifetimes are estimated to be transfered into the maintenance planning tool. The second software module corresponds to a simulation model for maintenance processes. By including peripheral data, the cost-optimal maintenance time is calculated on the basis of evaluated and previously defined decision alternatives.

The project aims to achieve three key results:

  1. Condition monitoring system for WT-powertrains for load-controlled operation and predictive maintenance
  2. Simulation module to determine the optimal maintenance time in the WF
  3. Software-based demonstrator for linking and illustrating the results of the calculation models

Branch

  • Energy/Water/Disposal/Recycling
  • IT, Software and Internet
  • Machinery and Plant Engineering
  • Automation and Measurement Engineering
  • Transport and Logistics
  • Associations
  • Research and Development

Topic Area

  • Service Management

Research Focus

  • Service Excellence

FIR Navigator

  • Smart Maintenance
  • Projectinfos

    Duration
    01.05.201831.12.2020
    Funding no.
    20028 N
    Funding information

    The IGF project 20028 N of the Institute for Industrial Management FIR e. V. at the RWTH Aachen University, Campus-Boulevard 55, 52074 Aachen is funded by the AiF within the framework of the program for the promotion of industrial joint research (IGF) by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag.