东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2003, Vol. 24 ›› Issue (8): 727-730.DOI: -

• 论著 • 上一篇    下一篇

基于神经网络的多传感器自适应滤波及其应用

伦淑娴;张化光;冯健   

  1. 东北大学信息科学与工程学院;东北大学信息科学与工程学院;东北大学信息科学与工程学院 辽宁沈阳　110004
  • 收稿日期:2013-06-24 修回日期:2013-06-24 发布日期:2013-06-24
  • 通讯作者: Lun, S.-X.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60274017);;

Multi-sensor adaptive filtering based on neural network for leak detection of pipeline

Lun, Shu-Xian (1); Zhang, Hua-Guang (1); Feng, Jian (1)   

  1. (1) Sch. of Info. Sci. and Eng., Northeastern Univ., Shenyang 110004, China
  • Received:2013-06-24 Revised:2013-06-24 Published:2013-06-24
  • Contact: Lun, S.-X.
  • About author:-
  • Supported by:
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摘要： 讨论了同一噪声源多传感信号神经网络自适应噪声抵消器的设计方法·利用神经网络自适应获取信息融合器LC的权系数,克服了采用基于平均法时可能失去部分信息造成信号估计误差太大的缺陷,较好地解决了多传感器信息融合的问题·该方法不仅能获得信号的最优估计而且能克服信号处理中存在模型扰动和噪声的不确定性等问题·为了检验该滤波方法的有效性,在输油管道的泄漏定位检测与诊断中,利用该滤波方法提高压力信号、流量信号等信噪比·结果表明,神经网络自适应噪声抵消器不仅实现简单,而且能快速、有效地消除流量、压力信号中的各种噪声·

关键词: 噪声抵消, 自适应滤波, 神经网络, 管道泄漏检测

Abstract: The low signal-to-noise ratio makes the signal processing of the leak detection of pipeline difficulty. The adaptive noise cancellation based on neural network is proposed to achieve the H2 optimal reconstruction and a desired robust against the effect of uncertainties in signal processing. In order to implement leak detection and location of pipeline correctly, multi-sensor signals are employed to overcome the shortcomings of creditability in case of single-sensor signal. The designed method can adjust the weights of linear combiner (LC) adaptively, and overcome the shortcomings of the method based on the averaging method of all sensor signals, which may lose accurate information and cause a large estimated error. The design method can not only obtain simplicity of implementation and conservation of operation time but also achieve better reconstruction performance than the method in the pressure and flow signal processing of the leak detection of pipeline.

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