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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lihui Zhao Huangang Wang Wenli Xu |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Automation, Tsinghua University, Beijing, China (Lihui Zhao; Huangang Wang; Wenli Xu) |
| Abstract | Optical Emission Spectra (OES) is a widely used signal in plasm etching. In this paper, an OES structural feature based fault detection method is proposed. Firstly, a template of normal OES curves is extracted via non-negative matrix factorization. Then singular points of the curves are detected by local matching based on the template. The magnitude and occurrence time of these singular points form a structural feature vector, which is a quantitative and simplified description of the curve's shape. Lastly, one-class SVM is introduced for generate a fault detection model based on structural feature vectors from normal OES curves. Experiments on an industrial benchmark dataset show that the proposed method is effective. |
| Starting Page | 971 |
| Ending Page | 976 |
| File Size | 200408 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467301985 |
| e-ISBN | 9781467301992 |
| DOI | 10.1109/ICSAI.2012.6223171 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines One-class SVM Structural Feature Fault detection Benchmark testing Feature extraction Vectors Etching Singular Point Template Matching Plasmas OES |
| Content Type | Text |
| Resource Type | Article |
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