A Soft Sensing Approach for Clothes Load Estimation in Consumer Washing Machines

Gian Antonio Susto, Giuliano Zambonin, Fabio Altinier, Elena Pesavento, Alessandro Beghi

Abstract: Fabric care home appliances are pervasive in houses worldwide and manufactures are constantly working for improving product performance, efficiency, and usability. From a manufacturing perspective, increase of performance has to be attained while minimizing the increase of production costs. In this context, a Soft Sensor for estimating the clothes load weight in a horizontal axis household washing machine is here presented. The proposed Soft Sensor is based on Machine Learning approaches. Several methodologies, both time-series and feature-based, are employed and compared. The approach has been tested on real world data on commercial household washing machines.