A Steam Detection Method for Liquor Distillation in the Process of Feeding

Abstract

Chinese liquor culture has a long history. The traditional liquor-making technology belongs to the labor-intensive industry with the characteristics of high labor intensity and low production efficiency. Especially in the process of feeding for liquor distillation, factitious material filling method is laborious and inefficient. Therefore, an intelligent control system is helpful for the process of material filling. The accuracy of steam detection result is the key factor determining the precision of adding material to the caldron. Corresponding to the characteristics of the moving robot arm and the light color and easy diffusion of the detected target steam in the process of adding material to the caldron, a steam detection method for adding material process is proposed in this paper. In the steam detection method, Firstly, suspected steam areas are detected by extracting motion characteristics, then, a feature fusion based BP neural network model is proposed to detect the steam in the suspected area. The proposed method is applied to the material filling process and the effectiveness is demonstrated.