SENSOR FUSION FOR REAL-TIME QUALITY EVALUATION OF BISCUIT DURING BAKING - COMPARISON BETWEEN BAYESIAN AND FUZZY APPROACHES

In industrial baking, operators control the oven mainly by subjective evaluation of the color of the cookies. To standardize the quality of cookies, it should be interesting to replace the operator's subjective evaluation of color by coupling a sensor and a data treatment tool li ke a classifier. With this aim, two different methods of classificatio n were tested and compared: a fuzzy and a Bayesian method. Two kinds o f results are presented: first, calibration and test points were used to establish the classifiers and second, a real time experiment was pe rformed in which comparison is provided between operator classificatio n and both fuzzy and Bayesian classifiers. The results for the two cla ssifiers are good and coherent (73% of good classification for the two classifiers). Nevertheless, the fuzzy classifier is better adapted to this problem. Indeed, the notion of color manipulated by the operator s is gradual and deterministic and not probabilistic. Furthermore, wit h such a fuzzy classifier it is possible to propose a computer-aided a lgorithm that allows a predictive diagnosis of the evaluation of the c lasses of color. Copyright (C) 1996 Elsevier Science Limited