Study on visual judgment method of fermentation degree in industrialized bread production based on BP neural network

Study on visual judgment method of fermentation degree in industrialized bread production based on BP neural network

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Objective: A BP neural network model was established to accurately determine the maturity of dough fermentation.Methods: Used machine vision technology to collect and process the read more pictures of bread fermentation process, obtained the quantitative information of the pictures, and a prediction model was established for bread fermentation degree based on BP neural network.Taking the time, area, instantaneous velocity, expansion rate, gray value energy, gray value relationship, gray value uniformity and gray value contrast as the input neurons, the regression model of relevant parameters was established.Results: The correlation between the above characteristic parameters and the fermentation process of bread was determined, which can effectively characterize the fermentation degree of bread; The results show that the accuracy of the prediction model based on BP neural network is 88.41%.

Conclusion: The model can kt196 torque converter accurately determine the degree of bread fermentation and effectively improve the quality consistency in industrial bread production.