Mass flow rate measurement of pneumatically conveyed particles based on power spectral density distribution of electrostatic signals

Measuring mass flow rate of particles in gas–solid two-phase flow is a practically challenging problem due to its complex dynamics. This study proposes a novel data-driven algorithm, utilizing the power spectral density (PSD) distribution of electrostatic signals of gas–solid two-phase flows, in order to analyze different flow conditions. The electrostatic signals induced by the charged particles at different positions and velocities in the pipeline have a unique power spectral density distribution. An electrostatic sensor was designed and an experimental investigation was conducted under varied operating conditions. The PSDs of measured signals under different experimental conditions were obtained. The PSD quantification analysis indicates that increasing the mass flow rate and conveying air velocity result in the PSD distribution expanding to higher frequencies and higher energy directions to varying degrees. A mapping relationship between the mass flow rate of the particles and the PSD features of the signals was established by quantifying the PSDs of signals under different flow conditions. The measurement error can be reduced to below 4 %.