Ultrasonic level scanning for monitoring mass flow of complex fluids in open channels — A novel sensor fusion approach using AI techniques

Open channel flow of complex fluids is found in many offshore applications and is currently monitored using Coriolis meters (good uncertainty with an expensive device) and simple paddle meters (very poor uncertainty). Recent publications in IEEE by the current authors indicate that the flow of complex fluids in open channels can be estimated by level measurements in the open channel by scanning the surface of the fluids in the open channel with an array of ultrasonic sensors. Complex fluids possess rheological properties dependent on flow, density, pipe dimensions etc. As an interesting industrial application of different types of sensors, this paper presents the basic configuration of the sensors used in a pilot scale study with some selected samples of complex fluids. A comparison of the performances of the sensors using coefficient of variations (CV) with respect to the mean values of the measurands is given as a preamble before using them in the final mass flow estimation. The group on multiphase studies in USN recently used various statistical parameters in the identification of flow regimes in multiphase flow studies as reported in the IEEE Sensors Community. In addition, the measurand values are filtered using different algorithms. The flow in the open channel is estimated using a Radial Basis Neural Network (RBNN) with the levels from the ultrasonic scanning array as inputs and the mass flow as output. The paper summarizes the findings with some indications of their implications to the offshore and other industries.