The gearbox is one of the key components in wind turbines. Gearbox fault signals are\nusually nonstationary and highly contaminated with noise. The presence of amplitude-modulated\nand frequency-modulated (AM-FM) characteristics compound the difficulty of precise fault diagnosis\nof wind turbines, therefore, it is crucial to develop an effective fault diagnosis method for such\nequipment. This paper presents an improved diagnosis method for wind turbines via the combination\nof synchrosqueezing transform and local mean decomposition. Compared to the conventional\ntime-frequency analysis techniques, the improved method which is performed in non-real-time can\neffectively reduce the noise pollution of the signals and preserve the signal characteristics, and hence\nis suitable for the analysis of nonstationary signals with high noise. This method is further validated\nby simulated signals and practical vibration data measured from a 1.5 MW wind turbine. The results\nconfirm that the proposed method can simultaneously control the noise and increase the accuracy of\ntime-frequency representation.
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