Method for optimizing multi-objective parameters based on fuzzy analysis and visualization technology

A parameter optimization and multi-objective technology, applied in the field of multi-objective parameter optimization, can solve problems such as non-linearity, difficult to screen out noise information, affect the judgment of operators, and distort data trends

Inactive Publication Date: 2012-10-10
镇江雅迅软件有限责任公司
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Problems solved by technology

Its shortcoming is that in the existing technology, it is difficult to screen out nonlinear and noise information, so that the final output data tends to be distorted, which affects the operator's judgment
[0063] The abo...

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  • Method for optimizing multi-objective parameters based on fuzzy analysis and visualization technology
  • Method for optimizing multi-objective parameters based on fuzzy analysis and visualization technology
  • Method for optimizing multi-objective parameters based on fuzzy analysis and visualization technology

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Embodiment Construction

[0099] In order to further illustrate the purpose and advantages of this patent, this patent will be further described below in conjunction with the accompanying drawings and specific implementation.

[0100] Taking the production process of butyl rubber as an example, the most direct factor affecting the quality of the product is the tensile strength (MPa) in the product testing process. In the case of a fixed formula, the main operating variables that affect product quality include: wind pressure (MPa), front roll temperature (°C), rear roll temperature (°C), vulcanization temperature (°C), vulcanization time (s) and vulcanization Pressure (MPa), etc. These 6 operating parameters were selected as variables, and the tensile strength of the product was selected as the optimization target, and 2 groups of 60 groups of historical data were recorded every day in April 2008 to conduct an optimization test on the example.

[0101] The optimization steps are as follows:

[0102] S...

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Abstract

The invention relates to a method for optimizing multi-objective parameters based on a fuzzy analysis and visualization technology, which provides an effective measure for processing, analysis, optimization and prediction of parameter data in an industrial process. The method comprises the following steps of: classifying the data by an evolution algorithm and the conventional fuzzy C average clustering hybrid algorithm to select an optimized data set; improving the conventional non-linear mapping evaluation function, introducing a distance error weight and a differentiation factor to ensure that a dimension reduction error of a distance between the farthest point and the nearest point in the data set is smallest to the greatest extent, concentrating the dimension reduction error on secondary information, procedurally solving by a fastest reduction method, and finally reducing high-dimensional spatial data to a two-dimensional plane; and finally, performing axis mapping on multi-dimensional data along each dimension, drawing contour lines, observing influences and optimization potentials of all the parameters on operating points to provide abundant intuitive information for people, repeatedly selecting the points, performing inverse mapping, and reducing to an actual operation space to fulfill the aim of parameter optimization.

Description

technical field [0001] The invention relates to a method for screening an optimal operation interval in an industrial process, in particular to a multi-objective parameter optimization method. Background technique [0002] In modern industrial production, due to the complexity of the process flow, many operating variables, high complexity of the system, and numerous influencing factors, the obtained production process parameter data is complicated, high-dimensional, nonlinear, and noisy, and difficult to obtain. Give people a clear and intuitive feeling. Therefore, it is difficult for people to effectively organize, analyze, judge and predict historical data. [0003] In response to the above problems, people often use classification and visualization methods to optimize and visualize the data structure. First, classify the data, remove outliers, select a set of optimal points, and then map the data to a two-dimensional plane. Display images on the plane, such as charts, h...

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Application Information

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IPC IPC(8): G05B13/04
Inventor 李骁淳鄢烈详林子雄卢海王志刚
Owner 镇江雅迅软件有限责任公司
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