| 宋伟,熊伟,董莎莎,谭建,彭波,吴娇,梁天佑,尹爱军.多元时间序列PCA分割及在天然气脱水装置工况识别中的应用[J].装备环境工程,2020,17(4):85-89. SONG Wei,XIONG Wei,DONG Sha-sha,TAN Jian,PENG Bo,WU Jiao,LIANG Tian-you,YIN Ai-jun.PCA Segmentation of Multivariate Time Series and Its Application in the Condition Identification of Natural Gas Dehydration Unit[J].Equipment Environmental Engineering,2020,17(4):85-89. |
| 多元时间序列PCA分割及在天然气脱水装置工况识别中的应用 |
| PCA Segmentation of Multivariate Time Series and Its Application in the Condition Identification of Natural Gas Dehydration Unit |
| 投稿时间：2019-07-05 修订日期：2019-09-05 |
| DOI：10.7643/issn.1672-9242.2020.04.014 |
| 中文关键词: 多元时间序列 PCA 序列分割 聚类 工况分离 |
| 英文关键词:multivariate time series PCA sequence segmentation parameter clustering separation of working conditions |
| 基金项目:重庆市重大主题专项重点研发项目(cstc2018jszx-cyztzxX0032)；中国石油重庆气矿科研项目(k18-11) |
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| Author | Institution |
| SONG Wei | Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing 400021, China |
| XIONG Wei | Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing 400021, China |
| DONG Sha-sha | Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing 400021, China |
| TAN Jian | Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing 400021, China |
| PENG Bo | Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing 400021, China |
| WU Jiao | Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing 400021, China |
| LIANG Tian-you | a.State Key Laboratory of Mechanical Transmissions, b.School of Mechanical Engineering, Chongqing University, Chongqing 400044, China |
| YIN Ai-jun | a.State Key Laboratory of Mechanical Transmissions, b.School of Mechanical Engineering, Chongqing University, Chongqing 400044, China |
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| 中文摘要: |
| 目的 建立不同的工作状态下的设备状态预测评估模型。方法 利用主成分分析法将多元时间序列数据进行切割，将分割后的数据段按照基于密度的方法，依照定义的距离，对多元时间序列进行聚类合并，从而得到不同工况下的时间序列。结果 按照脱水装置工况状态，将重沸器特征对应的多元时间序列划分为不同的数据段。结论 有效实现了脱水装置重沸器的参数数据分割，并识别出不同工况。 |
| 英文摘要: |
| The work aims to establish the equipment state prediction and evaluation models in the different conditions. The PCA method was used to cut the multivariate time series data, and the segmented data segments were clustered and merged according to the density-based method and the defined distance to obtain the time series under different conditions. According to the operating conditions of the dehydration unit, the multivariate time series corresponding to reboiler characteristics were divided into different data segments. The parameter data segmentation of the reboiler of the dehydration unit is effectively realized, and different working conditions are identified. |
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