BCMS
Observer-based condition monitoring system for main gears in wind power plants "BCMS"
Due to the continuous increase of power in off- and onshore wind power plants, the load on the single components is increasing. Furthermore, the cost for blackout time grows with the installed power. Condition monitoring systems (CMS) that are currently installed in wind power plants use a signal-based monitoring approach, at which impact sound serves as the processed signal. Due to their cost-efficiency and their ability to detect damage on fast spinning rolling bearings and gearing, signal-based systems are well established on the market. However, they are afflicted with some deficit when it comes to the detection of damage in slowly spinning components. Furthermore, the degree of automatization in CMS is relatively small, since the automatic generation of damage notifications does not work properly and requires an additional signal analysis performed by experts. In addition, the suitability of impact sound signals for life span assessments is limited, as these signals do not feature adequate correlation to essential dynamic load parameters.
Observer-Based condition monitoring system
Within this project, a novel and integrated state-acquisition and prediction system for main gears of wind turbines will be developed. Thereby, the information accuracy and volume of CMS in main gears of wind turbines should be increased and automated, and reliable damage notifications be enabled.
The BCMS that will be developed represents a combination of a model-based observer and a load-oriented sensor technology. The model will deduce parameters that are hard to measure from the attained process parameters.
By comparing the measured data to the results of the model-based calculation, predictions about the condition of gear components should be enabled. Thus, the chronology of local loads on gear wheels and rolling bearings can be determined in order to predict the remaining life span of the components. In this manner, the reliability of wind turbines should be increased and a condition-based maintenance be allowed. Thereby, maintenance incidents will become more projectable, which will result in downtime reduction for wind turbines and, therefore, in an increased energy yield.
Duration:
01.12.2015 - 30.11.2018
Projekt funded by:
Project promoted by: