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Research on the Application of Grey System Theory into the Batch Dyeing Process

Author: WangShunYan
Tutor: ZhangJianXin
School: Zhejiang University of Technology
Course: Measuring Technology and Instruments
Keywords: Grey System Theory Batch dyeing Dyeing rate modeling Temperature predictive control
CLC: TS193
Type: Master's thesis
Year: 2010
Downloads: 42
Quote: 0
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Abstract


China dyed goods producing countries, the batch dyeing my dyeing production. Modeling, and the temperature of the dye bath to achieve precise control of the dyeing process in batch dyeing process the dye is to increase the the batch dyeing automated production levels of key. However, due to the complexity of the batch dyeing mechanism are many factors that affect existing modeling and temperature control methods exist complex model of versatility and control accuracy of the modeling process. This article attempts will have less data and high accuracy characteristics of gray system theory is applied to a batch dyeing, establish the dye rate model and the dye bath temperature predictive control system to achieve the forecast and dye bath temperature of staining results precise control, thus helping to improve the staining product quality and staining the success rate, in order to achieve energy saving and efficiency purposes. Modeling respectively disperse dyes and direct dyes on dyeing rate model. First, the use of the the gray Verhulst model description temperature polyester swelling, joint Nernst adsorption isotherm model with the Arrhenius equation established on the basis of the reaction rate equation to disperse blue the RSE dyed polyester disperse dyes single factor (temperature) on the uptake rate model. Gray Verhulst model used is to create a the precise dyeing rate model key. Secondly, the use of GM (1,1) model, based on GM (1,1) and GM (0, N) model are two ways to establish a balance of direct light red F3B dye cotton dyeing percentage model, which is built the most important step in the dye uptake rate model. Then established on the basis of the adsorption rate equation the dyeing rate model of direct light red F3B dye cotton represented the direct dyes factors (temperature, electrolyte, pH). Two dyeing rate model has a high accuracy to meet the needs staining results predict. Easy to determine because of the use of gray system theory, the parameter values ??in the model, a small amount of calculation for the same type of dye to change the model of parameter values ??can be equally applicable. Temperature control gray GM (1,1) model and BP neural network is a combination of a gray neural network model (Grey Neural Network Model, referred GNNM) GNNM (1,1) to predict in advance of the system output. The multi-step prediction, rolling optimization and weighted feedback strategy, established GNNM (1,1) prediction PID temperature control system, the simulation results significantly better than in the three signals unit feedback PID control system.

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CLC: > Industrial Technology > Light industry,handicrafts > Textile industry,dyeing and finishing industry > Dyeing and finishing industry > Dyeing
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