The measurement of viscosity in rubber mixing process based on fuzzy-GA modeling
Rubber mixing is a complicated process and online measurement of viscosity is very difficult to achieve. To cope with the problem, a soft sensing approach based on fuzzy-GA modeling is proposed. During modeling, T-S fuzzy model is employed to approximate the non-linearity of rubber mixing process, an improved Gustafon-Kessel fuzzy clustering algorithm based on similarity assessing is proposed to determine the optimum number of clusters and real-coded GA (genetic algorithm) is adopted to optimize model parameters. All these techniques make the fuzzy model simple and accurate. Based on the approach, a test is conducted. The results show that the proposed approach provides a result near laboratory measurement, and the error is lower and acceptable. It decreases the time involved with tests in laboratory and can be seen as a powerful tool for online measurement of viscosity.