A Predicted Model Established Method for Spinning Yarn Quality in Cotton Mill

Qinge Wu, Yinghui Guo, Hu Chen, Yuangang Gao, Changsheng Fan


Many factors such as production environment, production process and raw material quality have certain influence on various yarn quality indicators. It is very difficult to control and predict accurate of yarn quality indicators. This paper proposed a multi-mode fuzzy inference system method. All the influencing factors parameters used as the input, and the yarn quality indicators as the output that to establish a relationship model between them. If the predicted data can’t satisfy the production requirements, the model needs to be calibrated. Compared this model with the existing methods, the data predicted by this model has some advantages, such as smaller error, higher precision, comprehension, and faster speed.


Fuzzy Speculation; Model Establishment; Evaluation Model; Calibration Model


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