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Backup page for Jan 26th

by Wenyu Zhao last modified 2011-06-06 11:28
IMS Wind Turbine Prognostics and Health Management (PHM) Technology Demonstration

Wind turbines are subjected to harsh operating conditions and are subjected to degradation. 20-25% of wind energy cost is due to operations & maintenance [1]. Predicting failures before happening and acting upon this information is essential for reducing the cost of wind energy generation and maintenance, especially for off-shore wind turbines.
Designing a reliable prognostics and health management system for wind turbines is very challenging due to the dynamic conditions faced by the turbines.
The IMS systematic approach provides a unique and systematic solution for wind turbine Prognostics and Health Management (PHM). In-particular the multi-regime approach for segmenting the data in each operating regime, followed by extracting features from the data and selecting different tools for different purposes.
In this demo, we will demonstrate the utilization of different health assessment, diagnostic and prognostic tools for wind turbines. In the demo a sample of gearbox data is used to illustrate the systematic methodology starting with the regime segmentation process, the selection of different prognostic tools and the selection of various information visualization tools.
Finite Element Analysis on 1.5MW Vertical Axis Wind Turbines


Finite Element Method (FEM), which is "a numerical technique for finding approximate solution of partial differential equation" [1], is widely applied in automotive, biomechanical, and aeronautical industries for designing new products, as well as predicting the properties and finding the root causes of failure. Using FEM, the cost and time of R&D can be greatly reduced.

In this simulation on1.5MW Vertical Axis Wind Turbines, FEM helps tremendously in evaluating vibration mode, weakest parts, buckling failure load and also in optimizing operation conditions, materials, and costs.   

Important Results

The following results are achieved from FEM. They can be feedback to improve the future design and are also important for condition monitoring of wind turbine operations.

(1) Resonance is less likely to occur when the rotating speed of VAWT is 15r/min ~ 20r/min;

(2) The structural stiffness of blades is the weakest in the entire wind turbine;

(3)The excitation frequencies of wind turbine are close to the first-order, third-order and fourth-order natural frequencies;

(4)The first-order critical buckling load is 12376kN.


[1] Finite Element Method,

 New demo


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