D-S evidence theory-based textile process data fusion system

Abstract

The invention discloses a D-S evidence theory-based textile process data fusion system. The system comprises sensor modules used for acquiring workshop data, local decision-making modules and a D-S synthesis module, wherein the sensor modules and the local decision-making modules are connected in a one-to-one correspondence manner; the local decision-making modules are connected with the D-S synthesis module; each local decision-making module adopts an adaptive weighted data fusion algorithm; and the D-S synthesis module adopts a D-S evidence theory. According to the system, two stages of sensors are adopted for information fusion; the first stage of the sensors are used for local fusion, a classic adaptive weighted fusion estimation algorithm is adopted, and the uncertainty and limitation of a single sensor are overcome, so that consistent explaination and description of a tested object are obtained; the second stage of the sensors are used for global fusion, and a D-S evidence theory is adopted; and the D-S evidence theory allows people to perform modeling on uncertain problems and perform reasoning, so that the uncertainty of things can be reflected more objectively.

Description

technical field [0001] The invention relates to the technical field of textile data monitoring, in particular to a textile process data fusion system based on D-S evidence theory. Background technique [0002] With the development of automation, networking and intelligentization of textile machinery and equipment, the entire textile manufacturing process generates a large amount of process equipment, production process and operation management data at an unprecedented speed, in addition to control loop data, text-type raw materials , sensor data, yarn defect detection image data and other unstructured data, and the data has high dimensionality, nonlinearity, strong correlation, and multi-noise characteristics, so the textile process data has a large amount of data, multiple types, strong real-time and The characteristics of great value basically have the characteristics of "4V" of big data, and it is a typical "big data". [0003] In this "big data" environment, the textile...

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Problems solved by technology

[0003] In this "big data" environment, the textile manufacturing execution system is a nonlinear, time-varying multivariate system, which makes the production process data often accompanied by unmeasurable uncertainties. As the application accuracy increases, it will increase geometrically, making it difficult for existing information integration models and methods to cope with this "big data", which ultimately makes it difficult to guarantee the correctness of the data fusion results in the textile process.

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