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Spaceflight product assembly quality problem classification method based on big data analysis

A technology of quality problems and classification methods, applied in the intersection of quality management and data mining

Inactive Publication Date: 2017-02-01
XIDIAN UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to provide a method for classifying aerospace product assembly quality problems based on big data analysis, aiming at solving the classification of quality problems. Based on the big data analysis platform, the quality can be predicted by analyzing various data in the manufacturing process of the enterprise. The type of problem

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  • Spaceflight product assembly quality problem classification method based on big data analysis
  • Spaceflight product assembly quality problem classification method based on big data analysis
  • Spaceflight product assembly quality problem classification method based on big data analysis

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Embodiment 1

[0034] The method for classifying aerospace product assembly quality problems based on big data analysis in the embodiment of the present invention includes the following steps:

[0035] The basic idea of ​​quality problem classification is as follows: figure 2 Shown: Build a big data analysis platform based on Hadoop, build an SVM model by combining influencing factors and historical quality problem data, use genetic algorithm to optimize the parameters of the SVM model, and use the classification accuracy of the SVM model as the fitness function in the genetic algorithm, If the classification accuracy of the SVM model meets the conditions or the genetic algebra meets the requirements, the parameters of the SVM model with the best classification accuracy are obtained, and the final GA-SVM model is also obtained; if the stop condition is not met, continue to optimize the model until it meets the requirements up to the request.

[0036] Step1: Build a big data analysis platfo...

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Abstract

The present invention discloses a spaceflight product assembly quality problem classification method based on big data analysis. The method comprises: constructing a big data analysis platform based on Hadoop, constructing an initial SVM model, utilizing genetic algorithm to perform optimization selection of the parameters of the initial SVM model, and obtaining the parameters of the optimal classification precision SVM model; and finally, obtaining a GA-SVM model. The GA-SVM model can classify different quality problems and has high classification precision. The spaceflight product assembly quality problem classification method based on the big data analysis utilizes the big data analysis technology to make the operation more effective, the crossover operation and the variation operation in the genetic algorithm consider the dynamic nature of the population evolution, the optimal solution can be rapidly and accurately found, and the genetic algorithm is applied to the optimization of the parameters of the support vector machine so as to improve the precision of the quality problem classification.

Description

technical field [0001] The invention belongs to the intersecting field of quality management and data mining, and in particular relates to a method for classifying assembly quality problems of aerospace products based on big data analysis. Background technique [0002] The so-called "assembly quality problems of aerospace products" refers to various quality problems that occur during the assembly process of aerospace products. The causes of quality problems are intricate, and different quality problems have different influencing factors. Factors are also related, and it is often difficult to determine the root cause of quality problems and the influencing factors that cause quality problems. The so-called "classification of aerospace product assembly quality problems" is to quickly and accurately analyze and diagnose the failures and quality problems that occur during the assembly process, and determine the nature, category and location of quality problems. With the intelli...

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Application Information

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IPC IPC(8): G06K9/62G06F17/30
CPCG06F16/182G06F16/285G06F2216/03G06F18/2411
Inventor 孔宪光常建涛刘洋洋殷磊马洪波王奇斌
Owner XIDIAN UNIV
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