Skip to main content
Windkraft
CMLB

Condition-Monitoring-Systems

Ongoing Project. Innovative condition monitoring systems for damage monitoring of swiveling large roller bearings.

 

Background Information

Renewable energies will ensure power supply in the future. According to the Ministry of Economic Affairs and Energy, as much as one-third of the power is generated from renewable sources already today. The plan of the Federal Government implies that by 2025 nearly one half of the power shall come from the renewable energy sources. In this context, wind power constitutes the largest part of green energy. Yet the expansion alone is not enough to ensure sustainable energy supply in the future. The existing systems require constant evaluation and enhancement to achieve this goal.

 

Objective

Real-time monitoring and predictive maintenance of machine components can significantly extend the service life and improve the efficiency of industrial installations. In wind power plants, roller bearers that connect the rotor hub with the rotor blade are particularly prone to wear. They enable tilting movements of rotor blades to allow their appropriate position in relation to the air flow, so that the system can achieve the best possible performance. The roller bearings here have been designed for continuous rotation, yet in practice, they are adjusted only in case of necessity in wind power plants. Due to this, minimal deformations occur, which, however, affect the performance of the entire wind power plant.

In the research project under the title “CMLB – Innovative Condition Monitoring Systems for Damage Monitoring in Swiveling Large Roller Bearings“, ASTRUM IT, Nuremberg Institute of Technology Georg Simon Ohm and the engineering company eolotec jointly develop an optical sensor-based condition monitoring system for roller bearings in wind turbines.

 

Schema_CLMB

Challenge for ASTRUM IT

In this project, ASTRUM IT provides software and infrastructure used for recording, storage and evaluation of measured data. The aim is to draw conclusions regarding the imminent damage as well as the required maintenance by means of evaluation of simple statistical key figures, real-time information or complex streaming data. On the basis of the recurring behavior patterns, preventive action for the future shall be additionally introduced. The software solution here makes use of the methods from artificial intelligence and data analysis. The entire concept is displayed on a cloud-based platform. ASTRUM IT as an experienced specialist in IT services provides the respective infrastructure for the research project.

The innovative monitoring system makes preventive maintenance possible. This can help to prevent breakdowns of wind power plants, and enhance their efficiency, profitability and service life into the bargain.

Sponsor

Bundesministerium für Bildung und Forschung

Project partners

POF-AC Th Nuernberg Logo
eolotec Logo