Mixing State Estimation of Peristaltic Continuous Mixing Conveyor with Distributed Sensing System Based on Soft Intestine Motion

Abstract

A peristaltic continuous mixing conveyor that focuses on the mechanism of the intestine has been developed as a technology for the mixing and transport of a solid-liquid mixture and high viscosity fluids. The developed peristaltic continuous mixing conveyor succeeded in the mixing and transport of such mixtures in a previous study. A simple cyclic pattern is currently used as the movement pattern of the system, and the control method can be further improved. In this study, we aim to realize an intelligent mixing and generation of a conveyor pattern based on intestinal movement. The mixing state of content during activation was estimated through machine learning. The results from the time-series measurement data show that an internal mixing state in three units of the peristaltic continuous mixing conveyor was estimated.