A Robust Algorithm to Detecting Wind Turbine Blade Health Using Vibro-Acoustic Modulation and Sideband Spectral Analysis

This paper presents a robust crack detection algorithm for wind turbine blades using vibroacoustic modulation and the area under the curve of the frequency spectrum of the sidebands. In a previous paper it was shown how the operational vibration of the turbine could be used as a pumping signal in vibro-acoustic modulation. However, the sources of the operational vibration frequencies are many and may change over time due to the change of the wind speed, direction and many other factors. Instead of trying to identify peaks in the spectrum of the sideband (a procedure that is error prone), the area under the curve of the sidebands around the probing signal is obtained. Utilizing the area under the curve allows the consideration of multiple operational vibration frequencies simultaneously in the analysis, making the algorithm more robust. By obtaining data simultaneously in all the turbine blades, the same operational vibration frequencies are applied to all blades. The area under the curve of the spectrum of the sidebands is then obtained and compared. If a large discrepancy exists in the area under the curve of the sidebands among the blades, then a potential crack is detected and signaled. In this paper the algorithm and its implementation are described in detail. Background Wind power is considered by many to be the most competitive source of renewable power. However, due to the high investment cost it is important to continuously monitor the health of the wind turbine and reduce the cost of unscheduled maintenance [1-2]. Additionally, the failure of a blade can cause damage in other subsystems and neighboring facilities [3]. Detecting early failure in wind turbines is very important to protect the investment cost of the wind farm. In this paper, a robust algorithm for crack detection is demonstrated using Vibro-Acoustic Modulation. In previous papers [4-5] it was shown how to use Vibro-Acoustic Modulation to detect cracks in turbine blades using a probing signal (Fprob) and a pumping signal (Fpump). A probing frequency such as a sine signal is introduced in the blade using a Micro Fiber Composite (MFC). In operational conditions, the wind turbine will produce a lower natural frequency called the pumping signal due to the rotation or the natural frequency response of the rotor and blades. Due to the nonlinearity introduced by a crack, modulation will occur at the probing frequency producing sidebands at Fprob + Fpump and Fprob – Fpump. These sidebands will be accentuated in the cracked blade due to the nonlinearity introduced by the cracked blade. Unfortunately, there are many sources of pumping frequencies that are not fixed and may change over time due to different factors such as: • The different modes of the turbine blades. • The rotational speed of the rotor. • The aerodynamic loading and how it causes deformations in the blades. These aspects make it difficult to identify a single peak for Fpump that can be analyzed. Instead of looking for a single Fpump peak, all Fpump sources are considered in the analysis by integrating the area in the spectrum over the range where these sidebands are likely to appear (Fpump_min , Fpump_max).