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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 12
3777-3780

Application of dynamic weighted SVDD based on difference in multi-modal process

Xie Yanhonga
Liu Wenjinga
Li Yuanb
a. Dept. of Mathematics & Physics, b. Process Fault Diagnosis Research Center, Shenyang University of Chemical Technology, Shenyang 110142, China
DOI: 10.19734/j.issn.1001-3695.2018.06.0402

Abstract

Traditional SVDD as a single-mode static fault detection algorithm is difficult to ensure the accuracy and real-time performance of multi-mode dynamic process fault detection. In order to solve this problem, this paper proposed a weighted dynamic SVDD monitoring method based on nearest neighbor difference(NND-DWSVDD). First, it used NND to eliminate the data multimodal structure and ensured that the process data obeyed the unimodal distribution. Then, it introduced the dynamic method for the data by difference process and added weights to highlight useful information. Finally, it established a monitoring model by using the SVDD method to achieve online monitoring. NND-DWSVDD improved the multi-modal dynamic process fault detection rate. For multimodal dynamic process fault detection, NND-DWSVDD didn't require multi-model modeling, and only needed a single model. It can meet single-modal fault detection requirements. Through multi-modal numerical example and semiconductor production process data, the results validate the effectiveness of the proposed method.

Foundation Support

国家自然科学基金面上项目(61673279,61490701)
辽宁省教育厅重点实验室基础研究项目(LZ2015059)
辽宁省自然科学基金资助项目(2015020164)
辽宁省教育厅一般项目(L2015432)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.06.0402
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 12
Section: System Development & Application
Pages: 3777-3780
Serial Number: 1001-3695(2019)12-055-3777-04

Publish History

[2019-12-05] Printed Article

Cite This Article

谢彦红, 刘文静, 李元. 基于差分的动态加权SVDD在多模态过程故障检测中的应用 [J]. 计算机应用研究, 2019, 36 (12): 3777-3780. (Xie Yanhong, Liu Wenjing, Li Yuan. Application of dynamic weighted SVDD based on difference in multi-modal process [J]. Application Research of Computers, 2019, 36 (12): 3777-3780. )

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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