东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2013, Vol. 34 ›› Issue (9): 1222-1226.DOI: -

• 信息与控制 • 上一篇    下一篇

基于LPV模型GRNN输气管道音波定位算法

王丽娜，高宪文，刘潭   

  1. (东北大学信息科学与工程学院，辽宁沈阳110819)
  • 收稿日期:2012-12-24 修回日期:2012-12-24 出版日期:2013-09-15 发布日期:2013-04-22
  • 通讯作者: 王丽娜
  • 作者简介:王丽娜(1985-)，女，辽宁台安人，东北大学博士研究生；高宪文(1954-)，男，辽宁盘锦人，东北大学教授，博士生导师.
  • 基金资助:
    国家自然科学基金重点资助项目(61034005).

Acoustic Location Algorithm in Gas Pipelines Based on the GRNN of LPV Model Approach

WANG Lina， GAO Xianwen， LIU Tan   

  1. School of Information Science ＆ Engineering， Northeastern University， Shenyang 110819， China.
  • Received:2012-12-24 Revised:2012-12-24 Online:2013-09-15 Published:2013-04-22
  • Contact: WANG Lina
  • About author:-
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摘要： 针对输气管道泄漏检测及定位问题以及管道内气体可压缩、检测难等特点，建立了输气管道线性变参数(LPV)模型，并设计了广义回归神经网络(GRNN)，以理论时间差为模型输入，以对应的管道各点位置为期望输出.采用音波法对输气管道进行泄漏故障诊断与定位.结合具体实例并采用现场数据进行仿真研究，结果表明:采用基于LPV模型的GRNN输气管道泄漏故障音波定位算法是一种有效的方法，可使预测值准确地跟踪真实值，实验结果为输气管道泄漏故障检测与定位的工业应用提供了可靠的依据.

关键词: LPV, GRNN, 输气管道, 故障检测与定位, 音波法

Abstract: Due to the problems of leakage detection and location in gas pipelines as well as the measurement difficulties for the gas in pipelines， a gas pipeline linear parameter varying (LPV) model was established， and the generalized regression neural network (GRNN) was designed， which took the theoretic time difference as input model， and the location of different point in pipes as output. Acoustic identification method was used for gas pipeline leakage fault diagnosis and location. Simulation was carried out using field data， and the results showed that acoustic location algorithm research in gas pipelines based on the GRNN of LPV model approach is an effective method， which can make the predictive value accurately track real value. The experimental results can provide the reliable basis for the industrial application of gas pipeline leak detection and location.

Key words: LPV, GRNN, gas pipelines, fault detection and location, acoustic method

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