Measuring bulk material flow—incorporating RFID and point cloud data processing

Abstract

A methodology incorporating radio frequency identification (RFID) and point cloud data processing to measure the mass flow of bulk material on the conveyor belt in real-time was developed and demonstrated. Specifically, a stereo vision camera was used to collect the point cloud data of the bulk material flow surface in a line-scanning way. Then, applying RFID technology to divide the belt into multiple test segments, the measurement bias caused by the slippage of the speed sensor’s friction wheel was eliminated significantly. Meanwhile, a volume flow measurement model which sequentially obtains the bulk material volume on each test segment in a space volume subtraction way was proposed. Then, given the issue that the bulk density of material flow is not fixed in real application scenarios, a determination model to dynamically estimate the porosity of material flow by point cloud processing was developed. Using this methodology, the measurement errors were within 2.2%.