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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 1
123-126

Fault detection of multi-mode batch process based on statistics difference LPP

Guo Jinyu
Zhong Lulu
Li Yuan
College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China
DOI: 10.19734/j.issn.1001-3695.2017.07.0665

Abstract

Aiming at non-Gaussian and multi-mode characteristics existed in industrial process data, this paper proposed a fault detection of multi-model batch process method based on statistics difference LPP. Firstly, it applied statistical pattern analysis to the batch process training data set to calculate the mean and variance of statistical process variables, and turned the uneven-length batches into equal-length statistics. It could ensure that the statistics pattern approximately obeyed the Gaussian distribution. Then it used the difference algorithm to transform the multi-mode into single mode. Finally, it used the LPP algorithm to reduce dimension and extract feature, and calculated the T2 statistic of the sample. And it used the kernel density estimation to determine the control limit. This paper projected the new test sample data onto the LPP model after statistics difference processing, and calculated the T2 statistics of the new data and compared them with the control limit for fault detection. Finally, the simulation results of the semiconductor process data show that this algorithm has the best fault detection effect, and demonstrates the effectiveness of the proposed algorithm.

Foundation Support

国家自然科学基金重大资助项目(61490701)
国家自然科学基金资助项目(61174119,61673279)
辽宁省教育厅重点实验室项目(LZ2015059)
辽宁省自然科学基金资助项目(201602584)
辽宁省教育厅资助项目(L2016007,L2015432)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.07.0665
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 1
Section: System Development & Application
Pages: 123-126
Serial Number: 1001-3695(2019)01-028-0123-04

Publish History

[2019-01-05] Printed Article

Cite This Article

郭金玉, 仲璐璐, 李元. 基于统计差分LPP的多模态间歇过程故障检测 [J]. 计算机应用研究, 2019, 36 (1): 123-126. (Guo Jinyu, Zhong Lulu, Li Yuan. Fault detection of multi-mode batch process based on statistics difference LPP [J]. Application Research of Computers, 2019, 36 (1): 123-126. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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