Mass Flow Measurement of Fine Particles in a Pneumatic Suspension Using Electrostatic Sensing and Neural Network Techniques

In this paper a novel approach is presented to the measurement of velocityand mass flow rate of pneumatically conveyed fine particles using electrostatic sensing and neural network techniques. A single ring-shaped electrostatic sensing and neural used to obtain a signal from which the twoo crucial parameters, velocity and mass flow rate of particles, may be derived for the purpose of monitoring nd control. It is found that the quantified characteristics of the signal are realted to the velocity and mass flow rate of particles. The relationships between the signal characteristics and the two measurands are established through the use of a back-propagation (BP) neural network. Results obtained the conjunction with a trained neural network may provide a simple, practical solution to the long standing industrial measurement problem.