Control Chart Pattern Recognition Based on Hybrid Model and Improved Multi-classification Mahalanobis-Taguchi System

被引:1
作者
Zhan J. [1 ]
Cheng L. [1 ]
Peng Z. [1 ]
Hu D. [2 ]
机构
[1] School of Economics and Management, Nanjing University of Science and Technology, Nanjing
[2] Nanjing Corad Electronic Equipment Co., Ltd., Nanjing
来源
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2019年 / 30卷 / 22期
关键词
Control chart; Improved multi-classification Mahalanobis-Taguchi system; Pattern recognition; Time series hybrid model;
D O I
10.3969/j.issn.1004-132X.2019.22.011
中图分类号
学科分类号
摘要
In order to improve intelligent monitoring level of product quality during the production, time series hybrid model and improved multi-classification Mahalanobis-Taguchi system were proposed to construct control chart pattern recognition algorithm. Firstly, time series hybrid model was applied to extract features for the control chart real-time data. Secondly, threshold calculation method was improved and multi-classification's discriminant was defined. Improved multi-classification Mahalanobis-Taguchi system was applied to reduce the dimension of features and recognize control chart patterns. Finally, to verify the validity of the algorithm, the public control chart dataset and manufacture cases were tested and the results were compared with other algorithms. Results indicate that an algorithm that is based on time series hybrid model and improved multi-classification Mahalanobis-Taguchi system may yield several successes including higher accuracy and simplify recognition system. Therefore, it is an effective method of control chart pattern recognition. © 2019, China Mechanical Engineering Magazine Office. All right reserved.
引用
收藏
页码:2716 / 2724
页数:8
相关论文
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