Abstract
This paper proposes new seismic-based methods for use in the wind energy industry with a focus on wind turbine condition monitoring. Fourteen Streckeisen STS-2 Broadband seismometers and two three-dimensional (3D) sonic anemometers are deployed in/near an operating wind farm to collect the data used in these proof-of-principle analyses. The interquartile mean (IQM) value of power spectral density (PSD) of the seismic components in 10 min time series is used to characterize the spectral signatures (i.e., frequencies with enhanced variance) in ground vibrations deriving from vibrations of wind turbine subassemblies. A power spectral envelope approach is taken in which the probability density function (PDF) of seismic PSD is developed using seismic data collected under normal turbine operation. These power spectral envelopes clearly show the energy distribution of wind-turbine-induced ground vibrations over a wide frequency range. Singular PSD lying outside the power spectral envelopes can be easily identified and is used herein along with supervisory control and data acquisition (SCADA) data to diagnose the associated suboptimal turbine operating conditions. Illustrative examples are given herein for periods with yaw misalignment and excess tower acceleration. It is additionally shown that there is a strong association between drivetrain acceleration and seismic spectral power in a frequency band of 2.5–12.5 Hz. The long-term goal of the research is development of seismic-based condition monitoring (SBCM) for wind turbines. The primary advantages of SBCM are that the approach is low-cost, noninvasive, and versatile (i.e., one seismic sensor monitoring multiple turbine components).
Published Version
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