A method for stabilizing the processing strength of a drum type silk drying machine
A yarn drying machine and drum-type technology, which is applied in the field of stabilizing the processing strength of the drum-type yarn drying machine, can solve the problems of poor real-time control ability of batch process, many influencing factors, large time and process span, etc.
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Embodiment 1
[0035] In a typical implementation of the present application, a method for stabilizing the processing strength of a drum-type silk drying machine is disclosed, and the mathematical model used is:
[0036] The mathematical model of moisture loss before and after the drying process is: Y1=X1-X2×Z+X3×N1+X4×N2, Y2=X5+X6×N3-X7×N4, where; Y1 is from the exit of moistening leaves to the entrance of drying silk The water content loss in the section, Y2 is the water content loss from the outlet of the dried silk to the mixed silk section, Z is the leaf storage time after moistening, N1 is the ambient temperature from the exit of the moistening leaf to the entrance of the drying silk, and N2 is the section from the exit of the moistening leaf to the entrance of the drying silk Ambient humidity, N3 is the ambient temperature from the drying silk export to the mixed silk section, N4 is the ambient humidity from the drying silk export to the mixed silk section, X1, X2, X3, X4, X5, X6, X7 a...
Embodiment 2
[0040] A system for stabilizing the processing strength of a drum type silk drying machine, comprising a dynamic prediction system for the processing strength of silk drying, the dynamic prediction system for the processing strength of silk drying communicates with a measurement system and a production central control system, the measurement system is an environment temperature and humidity acquisition module and Historical data analysis module;
[0041]Further, the ambient temperature and humidity acquisition module simulates the distribution of the ambient temperature and humidity inside the production workshop, preferably at a height of 1.5±0.3m as the installation plane, and selects a process route that can characterize the temperature and humidity changes in this area in combination with the process route where the moisture content is lost. The area is the installation point, and finally through the data fusion of the dynamic prediction system of the drying processing inte...
Embodiment 3
[0045] Taking a certain brand of cigarettes as an example, the analysis is carried out in units of historical months. Collect the water loss value and the environmental temperature and humidity value of the water loss point of all batches from November 1, 2017 to 30, and perform regression analysis to determine the mathematical model, Y1=-0.365-0.006*leaf storage time+0.059*internal temperature -0.006*internal humidity; Y2=1.192+0.005*internal temperature-0.012*internal humidity.
[0046] After the validity test of the model, the water loss regression model is significant, and the residual and mean square tests are normal. Finally, the regression equation of the water loss point in November 2018 is obtained, and the regression equation is used to predict and control the moisture at the outlet of the leaves:
[0047] Moisture content Q1 at moist leaf outlet = standard center value of mixed silk moisture content Q3 + Y2 + brand drying dehydration target value + Y1. For example, ...
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