Color spinning process quality control model construction method based on knowledge automation technology

Abstract

The present invention discloses a color spinning process quality control model construction method based on a knowledge automation technology. The method comprises the following steps of designing a parallel cuckoo search algorithm based on particle swarm optimization, carrying out the high dimensional data feature extraction, and further utilizing a self-organizing neural network theory to solve the optimal solution of the knowledge variables; on the basis of the above steps, utilizing a grey system theory, a cooperative training algorithm and a support vector machine to construct a relation matrix between the knowledge variables, and utilizing a method of mean value to solve the association degree, and further designing a support vector regression algorithm based on the cooperative training, and automatically correcting an association degree calculation result; on the basis of the above two steps, utilizing the support vector machine to construct a color spinning process quality control model based on the knowledge automation technology. According to the present invention, the color spinning process quality control model based on the knowledge automation technology is constructed, the working efficiency is improved, at the same time, the data preparation is convenient.

Description

technical field [0001] The invention relates to the field of textiles, in particular to a method for constructing a color spinning process quality control model based on knowledge automation technology. Background technique [0002] The color spinning industry is a sunrise industry in the textile industry, and its products have been widely used in many fields such as environmental protection, special military supplies and aerospace. But unfortunately, due to the bottleneck problems in the color spinning manufacturing process, such as imprecise control of the underlying equipment, lack of multi-domain knowledge correlation analysis, and low degree of automation integration, such as upper-level planning and scheduling, it seriously restricts the innovation and development of color spinning enterprises. [0003] As far as the color spinning intelligent manufacturing process is concerned, the traditional "spinning first and then dyeing" process has been fundamentally subverted, ...

AI Technical Summary

Problems solved by technology

However, there is little research on the nature of knowledge automation, even whether knowledge automation should exist and be attached to manufacturing systems, and whether other work system platforms are more suitable for knowledge automation management.

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