基于经验模态分解的织造过程数据拟合方法的应用

Application options of data fitting methods in weaving process based on Empirical Mode Decomposition

为提高织造过程中的纺织品品质,以保证整个制造过程的连续性,首先,对已有监控系统的应用情况进行分析;然后,针对系统在数据拟合处理和异常情况预警方面的不足,对织造过程中的不确定性原因进行深入研究,并对系统已使用的软件滤波算法进行比较分析。基于此,借助经验模态分解(EMD)方法对织造过程数据进行去噪实验比较,以及拟合结果仿真。结果表明:基于EMD的数据拟合方法能更准确地保证织造过程数据的正确性,有利于提高纺织品的品质和整个制造过程的连续性。

To improve the quality of textile weaving process and guarantee the continuity of the entire manufacturing process, first, the application of the existing monitoring system was analyzed. Then, for the system deficiencies in data fitting and processing, and abnormal cases warning, the uncertainty factors in the manufacturing process were studied, and the software filtering algorithms in use for the system were analyzed. Furthermore, through using Empirical Mode Decomposition （EMD） , denoising experiments on weaving process data were compared, and the fitting results were simulated. Practice has proved that EMD-based method can effectively ensure the accuracy of production data, improve the quality of textiles, and guarantee the continuity of the entire manufacturing process.