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

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.