Fault detection based on robust principal component analysis with a novel data compression method in the pumping unit.pdf
文献类型：会议论文
| 作者 | Pan YJ(潘怡君)1,2,3 ; An RQ(安汝峤)4; Zheng ZY(郑泽宇)1,2,3,4; Fu DZ(付殿峥)1,2,3
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| 出版日期 | 2021 |
| 会议日期 | October 27-30, 2021 |
| 会议地点 | Chengdu, China |
| 关键词 | fault detection data compression pumping unit robustness |
| 页码 | 1-6 |
| 英文摘要 | There are many displacement and load data in a dynamometer card, and the calculation is complicated. Moreover, some process measured variables in the pumping unit are collected during the production with abundant information. In this paper, a method for dynamometer card compression is proposed, and five important variables are adopted for constructing the process monitoring model. Furthermore, the robust principal component pursuit method is used for fault detection for the oil production process, and the T2 statistic is calculated. In final, the effectiveness of the proposed method is proved by a numerical example and an oil production process. |
| 产权排序 | 1 |
| 会议录 | The 11th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering & The 4th International Conference on Reliability Systems Engineering (QR2MSE 2021 & ICRSE 2021)
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| 源URL | [http://ir.sia.cn/handle/173321/29961]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 通讯作者 | Pan YJ(潘怡君) |
| 作者单位 | 1.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China 3.Digital Factory Department, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 4.Advanced Institute of Information Technology, Peking University, Hangzhou, China 5.University of Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Pan YJ,An RQ,Zheng ZY,et al. Fault detection based on robust principal component analysis with a novel data compression method in the pumping unit.pdf[C]. 见:. Chengdu, China. October 27-30, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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