Signal processing techniques for the identification of wheels’ imbalance in presence of disturbances

Abstract

This work compares different digital signal processing methods for the extraction of the fundamental harmonic (1X) from noisy signals. Aim of the comparison is the identification of the best technique to measure the rotor imbalance in presence of mechanical disturbances. Four methods have been selected after the literature review: the Hilbert Vibration Decomposition (HVD), the Hilbert Huang Transform (HHT), the Wavelet Packet Decomposition (WPD) and the ordinary Fourier Transform paired with computed order tracking (COT-FT). The four methods performances were compared analyzing measurements performed in different conditions. Factorial design of experiments was used to identify the effect of the rotor size (car wheels with different diameters), of the imbalance (5, 20 and 60 g applied to the rim), of the balancing machine (two types with different mechanical characteristics) and of the type of disturbance. Globally, 216 imbalance measurements were performed. The dynamic forces measured by two piezoelectric load cells were analyzed with the four proposed methods. Results evidenced the good performances of the WPD and COT-FT. Uncertainty benefits deriving from the analysis of more than 4 revolutions are generally negligible. The possibility of merging the indications of different methods is proposed and discussed.