Kalman Filtering for Precise Mass Flow Estimation on a Conveyor Belt Weigh System

Abstract

Conveyor belt weigh systems are widely used worldwide in industry for mass flow estimation. This paper investigates the application of Kalman filtering for tachometer response correction and thus accurate flowrate measurement. The tachometer is a sensor with a pulse-train output with a frequency proportional to the conveyor belt rpm. Under harsh conditions, as are generally found in the industry, the pulse-width of the tachometer output is susceptible to noise, thus corrupting the conveyor belt’s speed measurement. Thus, a Kalman filter has been employed for accurate estimation of the conveyor belt speed, and thus, the mass-flow estimate. To facilitate this investigation, the belt conveyor system (plant) and the Kalman filter were initially modeled and simulated in MATLAB Simulink. This was followed by development of the Kalman filter based mass flow estimator on a Zynq-7000 based Digilent Zedboard, and interfacing it with a Speedgoat Realtime Target Machine (RTM) on which the plant model ran in real-time. The results are presented at the end, demonstrating the effectiveness of the proposed estimation technique implemented on actual hardware.