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First of all, data processing is carried out to convert the collected vibration monitoring data into RMS Using the average method of adding the window to denoise the generated raw data, and then adding the window Fourier transform of the noise reduction data, the time domain signal is converted into a frequency domain signal to obtain the spectrogram. Finally, Spectrum analysis is carried out to determine the fault location according to the spectral characteristics of the spectrum and combined with the actual verification. According to the experimental results and then combined with the example analysis, a certain early warning strategy, used for the future parts of the turbine may fail to early warning, reducing the cost of operation and maintenance. The offshore wind turbine fault diagnosis method proposed in this paper can effectively diagnose a variety of faults in various parts of offshore wind turbines, and make full use of big data to improve diagnostic accuracy. |
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Vibration
Windows
Environmental monitoring
Wind turbine technology
Wind energy
Fourier transforms
Signal processing
