Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization
文献类型：期刊论文
| 作者 | Gu, Nong1; Cao, Zhiqiang2 ; Xie, Liangjun3; Creighton, Douglas1; Tan, Min2; Nahavandi, Saeid1
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| 刊名 | JOURNAL OF INTELLIGENT MANUFACTURING
 |
| 出版日期 | 2013-12-01 |
| 卷号 | 24期号:6页码:1241-1252 |
| 关键词 | Control charts Concurrent patterns Singular spectrum analysis Learning vector quantization networks Aluminium smelting |
| 英文摘要 | Identification of unnatural control chart patterns (CCPs) from manufacturing process measurements is a critical task in quality control as these patterns indicate that the manufacturing process is out-of-control. Recently, there have been numerous efforts in developing pattern recognition and classification methods based on artificial neural network to automatically recognize unnatural patterns. Most of them assume that a single type of unnatural pattern exists in process data. Due to this restrictive assumption, severe performance degradations are observed in these methods when unnatural concurrent CCPs present in process data. To address this problem, this paper proposes a novel approach based on singular spectrum analysis (SSA) and learning vector quantization network to identify concurrent CCPs. The main advantage of the proposed method is that it can be applied to the identification of concurrent CCPs in univariate manufacturing processes. Moreover, there are no permutation and scaling ambiguities in the CCPs recovered by the SSA. These desirable features make the proposed algorithm an attractive alternative for the identification of concurrent CCPs. Computer simulations and a real application for aluminium smelting processes confirm the superior performance of proposed algorithm for sets of typical concurrent CCPs. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Manufacturing |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | INDEPENDENT COMPONENT ANALYSIS ; NEURAL-NETWORK APPROACH ; BLIND-EQUALIZATION ; RECOGNITION ; CRITERION ; PARAMETERS ; ALGORITHM ; SYSTEM |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000326297800014 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3503]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 作者单位 | 1.Deakin Univ, Ctr Intelligent Syst Res, Waurn Ponds, Vic 3216, Australia 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Schlumberger Ltd, Houston, TX 77073 USA |
| 推荐引用方式 GB/T 7714 | Gu, Nong,Cao, Zhiqiang,Xie, Liangjun,et al. Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization[J]. JOURNAL OF INTELLIGENT MANUFACTURING,2013,24(6):1241-1252. |
| APA | Gu, Nong,Cao, Zhiqiang,Xie, Liangjun,Creighton, Douglas,Tan, Min,&Nahavandi, Saeid.(2013).Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization.JOURNAL OF INTELLIGENT MANUFACTURING,24(6),1241-1252. |
| MLA | Gu, Nong,et al."Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization".JOURNAL OF INTELLIGENT MANUFACTURING 24.6(2013):1241-1252. |
入库方式： OAI收割
来源：自动化研究所
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