Nonlinear contour data monitoring method based on LLE-SVDD

A technology of LLE-SVDD and outline data, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems affecting the monitoring accuracy and monitoring effect, and achieve the goal of keeping the topology unchanged and solving the disaster of dimensionality Effect

Inactive Publication Date: 2020-12-15
ZHENGZHOU UNIV
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Problems solved by technology

In these high-dimensional nonlinear contour data, there are a lot of redundant information and irrelevant information. If such high-dimensional contour data are directly monitored, it will inevitably affect the accuracy and effect of monitoring.

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  • Nonlinear contour data monitoring method based on LLE-SVDD
  • Nonlinear contour data monitoring method based on LLE-SVDD
  • Nonlinear contour data monitoring method based on LLE-SVDD

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[0038] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0039] Such as Figure 1 to Figure 3 Shown, a kind of nonlinear contour data monitoring method based on LLE-SVDD of the present invention comprises the following steps:

[0040] S1. Local linear embedding dimensionality reduction: In order to reduce the dimensionality of high-dimensional nonlinear contour data, a local linear embedding (LLE) algorithm is introduced. The advantage of this algorithm is that it can maintain the structural relationship between nonlinear contour data in the neighborhood. The contour data of the nearest neighbor in the high-dimensional space is also the nearest neighbor in the low-dimensional embedding; the steps of using the LLE algorithm to r...

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Abstract

The invention relates to the technical field of data monitoring, in particular to a nonlinear contour data monitoring method based on LLE-SVDD, shows that the nonlinear contour monitoring model basedon LLE-SVDD has a good monitoring effect by comparing the effect of the this method with the monitoring effect of a traditional contour monitoring method, and provides a new visual angle and a new method for further exploring the nonlinear contour quality real-time monitoring problem. The method comprises the steps of performing S1, local linear embedding dimension reduction; S2, constructing an LLE-SVDD nonlinear quality monitoring model; and S3, carrying out a model monitoring process.

Description

technical field [0001] The invention relates to the technical field of data monitoring, in particular to an LLE-SVDD-based nonlinear contour data monitoring method. Background technique [0002] Due to the large amount of data collected in the complex product monitoring process and the complex relationship, it is more accurate to use a certain functional relationship to describe the relationship between independent variables and quality characteristics than univariate or multivariate variables. Therefore, this complex functional relationship between a single response variable and multiple explanatory variables is called a profile. At present, there are three main methods for monitoring nonlinear profiles, the monitoring method based on regression fitting, the monitoring method based on difference measurement, and the monitoring method based on machine learning. [0003] The control method based on regression fitting is to carry out regression fitting to the nonlinear contou...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/21355G06F18/2411G06F18/22G06F18/214
Inventor 刘玉敏梁晓莹赵哲耘
Owner ZHENGZHOU UNIV
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