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A Novel Strong Tracking Fault Prognosis Algorithm

机译：一种新的强跟踪故障预测算法

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摘要

Improving the ability to track abruptly changing states and resolving the degeneracy are two difficult problems to particle filter applied to fault prognosis. In this paper, a novel strong tracking fault prognosis algorithm is proposed to settle the above problems. In the proposed algorithm, the artificial immunity algorithmis first introduced to resolve the degeneracy problem, and then the strong tracking filter is introduced to enhance the ability to track abruptly changing states. The particles are updated by strong tracking filter, and better particles are selected by utilizing the artificial immune algorithm to estimate states. As a result, the degeneracy problem is resolved and the accuracy of the proposed fault prognosis algorithmis improved accordingly. The feasibility and validity of the proposed algorithm are demonstrated by the simulation results of the standard validation model and the DTS200 system.
机译：改善跟踪突然变化的状态的能力并解决退化问题是将粒子过滤器应用于故障预测的两个难题。为了解决上述问题，本文提出了一种新的强跟踪故障预测算法。在提出的算法中，首先引入了人工免疫算法来解决退化问题，然后引入了强跟踪滤波器以增强对突变状态的跟踪能力。通过强跟踪滤波器更新粒子，并通过使用人工免疫算法估计状态来选择更好的粒子。结果，解决了退化问题，并因此提高了所提出的故障预测算法的准确性。通过标准验证模型和DTS200系统的仿真结果证明了该算法的可行性和有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第10期|676289.1-676289.10|共10页
  • 作者

    Zhang Qi; Jiang Wei; Li Tian-Mei; Zheng Jian-Fei;

  • 作者单位

    Xian Res Inst High Tech, Unit 302, Xian 710025, Peoples R China.;

    Xian Res Inst High Tech, Unit 302, Xian 710025, Peoples R China.;

    Xian Res Inst High Tech, Unit 302, Xian 710025, Peoples R China.;

    Xian Res Inst High Tech, Unit 302, Xian 710025, Peoples R China.;

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