王雪莉, 党瑞, 周琰, 孙巍, 王海明, 刘路, 田孝忠, 张志环. 基于压力波的清管器在线定位算法[J]. 油气储运, 2017, 36(3): 290-296. DOI: 10.6047/j.issn.1000-8241.2017.03.009
引用本文: 王雪莉, 党瑞, 周琰, 孙巍, 王海明, 刘路, 田孝忠, 张志环. 基于压力波的清管器在线定位算法[J]. 油气储运, 2017, 36(3): 290-296. DOI: 10.6047/j.issn.1000-8241.2017.03.009
WANG Xueli, DANG Rui, ZHOU Yan, SUN Wei, WANG Haiming, LIU Lu, TIAN Xiaozhong, ZHANG Zhihuan. Online pig positioning algorithm based on pressure wave[J]. Oil & Gas Storage and Transportation, 2017, 36(3): 290-296. DOI: 10.6047/j.issn.1000-8241.2017.03.009
Citation: WANG Xueli, DANG Rui, ZHOU Yan, SUN Wei, WANG Haiming, LIU Lu, TIAN Xiaozhong, ZHANG Zhihuan. Online pig positioning algorithm based on pressure wave[J]. Oil & Gas Storage and Transportation, 2017, 36(3): 290-296. DOI: 10.6047/j.issn.1000-8241.2017.03.009

基于压力波的清管器在线定位算法

Online pig positioning algorithm based on pressure wave

  • 摘要: 传统清管器跟踪定位技术受管道及周围环境条件限制不具有通用性,而基于差压法的清管器跟踪定位技术因所采集的压力信号变化灵敏、不受外界因素影响等优势获得了越来越多的关注,但针对该技术定位算法的研究较少。基于差压法的清管器在线跟踪定位技术,以中国石油管道公司长沙输油气分公司武汉输油站清管作业为例,提出了基于压力波的清管器在线定位算法。该算法的实现分为3步:①分析清管过程中采集的压力信号,将其划分5种信号状态,包括压力平稳状态、清管器通过阀室状态、压力升高状态、压力降低状态及清管器卡堵状态;②采用小波奇异性检测和相关性分析的方法实现不同压力信号状态的识别;③确定清管器在线定位算法,包括正常运行定位算法和卡堵定位算法。利用实采数据模拟清管过程验证该算法的有效性,结果表明该算法定位准确,可实现清管器清管的全过程监测。

     

    Abstract: The traditional pig tracking and positioning technologies can not be applied universally due to the restriction of pipelines and surrounding environments. The pig tracking and positioning technology based on differential pressure attracts more and more attention owing to its advantages of sensitive pressure signals and surrounding influence independence, but its positioning algorithm is less studied. In this paper, the online pig positioning algorithm based on pressure wave was proposed for the differential pressure based pig tracking and positioning technology by taking the pigging operation in Wuhan oil transfer station, Changsha Oil & Gas transportation Sub-company of PetroChina Pipeline Company as an example. The algorithm is divided into three parts. Firstly, the signals acquired during the pigging are analyzed and divided into five states, i.e., stable pressure, pig passing valve chamber, increasing pressure, decreasing pressure and struck pig. Secondly, the states of pressure signals are distinguished by means of wavelet singularity detection and correlation analysis. And thirdly, the online pig positioning algorithm is worked out for normal operation and struck state. The algorithm was verified by using the data acquired on site. It is shown that this online pig positioning algorithm can position the pigs accurately and monitor the whole process of pigging operation.

     

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