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Precise extraction of sinusoidal vibration parameters is essential for thedynamic calibration of vibration sensors, such as accelerometers. However,several standard methods have not yet been optimized for large backgroundnoise. In this work, signal processing methods to extract small vibrationsignals from noisy data in the case of accelerometer calibration is discussed.The results show that spectral leakage degrades calibration accuracy. Threemethods based on the use of a filter, window function, and numericaldifferentiation are investigated with theoretical calculations, simulations,and experiments. These methods can effectively reduce the contribution of thecalibration system noise. The uncertainty of micro vibration calibration in theNational Metrology Institute of Japan is reduced by two orders of magnitudesusing the proposed methods. The theoretical analyses in this work can lay thefoundation for the optimization of signal processing in vibration calibration,and can be applied to other dynamic calibration fields.

Precise sinusoidal signal extraction from noisy waveform in vibration calibration