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| Optimization of peanut extrusion parameters based on BP neural network |
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| KeyWord:peanut extrusion BP neural network |
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| Abstract: |
| The effects of peanut extrusion parameters on product quality (residual oil rate of the meal) were studied. Through the establishment of BP neural network model, the samples were trained to have the mapping ability of process parameters-product quality. Combined with PSO, the optimal parameter combination was determined when the residual oil rate of the meal was the lowest. The results showed that BP neural network model was established and the relevant experiments verified the simulation results, which showed that BP neural network model had effectiveness and adaptability in parameter optimization. The optimal parameter combination was obtained as follows: spindle speed 55 r/min, diameter of die orifice 12 mm, sleeve temperature 105?℃, screw speed 26 r/min, moisture content 11% and distance between die and screw 12 mm. Under these conditions, the residual oil rate of the meal was 1.03%. The diameter of die orifice, spindle speed and sleeve temperature had higher effects on the product quality. |
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