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On this work, the experimental implementation of a cascade control algorithm to regulate coffee roasting degree in a batch spouted bed process is presented. The control algorithm is composed of an inner control loop that regulates the temperature of the hot air inflow used to roast coffee grains inside a spouted bed, while an outer control loop, based on imaging processing techniques, tracks on real time the coffee roasting degree and decides if the inflow air temperature must be modified. To achieve this goal, a colour-matching algorithm is used to compare a colour spectrum obtained from images acquired on real time, from a peephole on the spouted bed, with the colour spectrums of several reference images with different degrees of roasting. Match scores are computed based on the similarity between the colour spectrums. With the match scores, a roasting index is finally calculated to assess the degree of roasting, allowing to automatically track the roasting progress to decide if the batch roasting process has achieved the desired roasting degree. The experimental results show that the control scheme is able to robustly achieve the desired roasting degree with excellent effectiveness.

Cascade Control of Coffee Roasting Degree in a Spouted Bed Batch Process Based on a Real-Time Imaging Analysis