Bayesian online change point detection method for process monitoring
文献类型：会议论文
| 作者 | Pan YJ(潘怡君)1,2,3 ; Zheng ZY(郑泽宇)1,2,3
|
| 出版日期 | 2020 |
| 会议日期 | August 22-24, 2020 |
| 会议地点 | Hefei, China |
| 关键词 | fault detection Bayesian change point detection industrial process exponential family |
| 页码 | 3389-3393 |
| 英文摘要 | Aiming at the problem of a large amount of unlabeled observations collected in the industrial processes, an unsupervised Bayesian online change point detection method is adopted for fault detection. Firstly, a prior probability of fault occurrence is set based on the significance level. Secondly, the predictive distribution is calculated using the exponential family likelihoods as a new observation arrives. Finally, based on the observed data, a recursive message-passing algorithm is applied for calculating the fault occurrence probability at the current sampling point. The power of the Bayesian method for fault detection is tested in a numerical simulation and the Tennessee-Eastman (TE) process. |
| 源文献作者 | IEEE Control Systems Society (CSS) ; Northeastern University ; State Key Laboratory of Synthetical Automation for Process Industries ; Technical Committee on Control Theory, Chinese Association of Automation |
| 产权排序 | 1 |
| 会议录 | Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-5854-9 |
| WOS记录号 | WOS:000621616903085 |
| 源URL | [http://ir.sia.cn/handle/173321/27697]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 通讯作者 | Zheng ZY(郑泽宇) |
| 作者单位 | 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 3.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Pan YJ,Zheng ZY. Bayesian online change point detection method for process monitoring[C]. 见:. Hefei, China. August 22-24, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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