DWT-based adaptive decomposition method of electrostatic signal for dilute phase gas-solid two-phase flow measuring

Abstract The inner flush-mounted electrostatic sensors are widely used for measuring gas-solid two-phase flow in many industries. The measured signal contains induced charge signal (ICS) and transferred charge signal (TCS). According to the band characteristics of the ICS, an adaptive decomposition method based on discrete wavelet transform (DWT) is proposed to extract ICS from measured signals of the sensors. In the measurement of the cross-correlation particle velocity, the mean cross-correlation coefficient between the extracted ICS from upstream and downstream electrodes is 0.74, increased from the previous coefficient 0.48 between the overall measured signals collected from the electrodes. This significant increase shows that the ICS better serves the measurement with higher accuracy. Meanwhile, the mean relative standard deviation (RSD) of the solid velocity is reduced from 3.35% to 2.69% after decomposition, which brings better stability. In addition, the root-mean-square (RMS) of the extracted TCS shows a trend of linear increase as the solid mass flow rate and superficial air velocity rise, indicating that TCS can also serve as an effective method to predict the solid mass flow rate as an alternative to ICS.