Prediction of Wort Density with LSTM Network

TL;DR

This article introduces a system that helps the brewer measure wort density through sensors in order to reduce errors in manual data collection using a neural network, known as LSTM.

Abstract

Many physical target values in technical processes are error-prone, cumbersome, or expensive to measure automatically. One example of a physical target value is the wort density, which is an important value needed for beer production. This article introduces a system that helps the brewer measure wort density through sensors in order to reduce errors in manual data collection. Instead of a direct measurement of wort density, a method is developed that calculates the density from measured values acquired by inexpensive standard sensors such as pressure or temperature. The model behind the calculation is a neural network, known as LSTM.

Figures (23)

• Figure 1: Architecture
• Figure 2: Brewing Process
• Figure 3: Brew Container
• Figure 4: Fermentation Containers
• Figure 5: Fermentation Process