Tachometer-Less Synchronous Sampling for Large Speed Fluctuations and Its Application in the Monitoring of Wind Turbine Drive Train Condition

Abstract

Accurate shaft speed extraction is crucial for synchronous sampling in the fault diagnosis of wind turbines. However, traditional narrow-bandpass filtering techniques face limitations when dealing with large fluctuations in rotational speed, hindering the accurate construction of an instantaneous phase for synchronous resampling of a shaft. To overcome this, we propose a tachometer-less synchronous sampling based on Scaling-Basis Chirplet Transform, tailored to a wind turbine’s structure and operating conditions. The algorithm generates a time–frequency representation of the vibration response, revealing time-varying characteristics even under large speed fluctuations. Using maximum tracking on the time–frequency spectrum, we extract instantaneous speed and compare its accuracy with tachometer-acquired results. The instantaneous phase is obtained through numerical integration, and vibration data are resampled synchronously using inverse function interpolation in the digital domain. Numerical simulations and practical cases of wind turbines demonstrate the effectiveness and the engineering applicability of our methodology.