舰船主动力装置故障隔离与参数估计方法
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国家自然科学基金资助项目(51579242)


Fault isolation and parameter estimation of marine main power plant based on bicausal bond graphs
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    摘要:

    针对舰船主动力装置结构复杂、故障种类多和系统不确定性等故障诊断问题,提出采用基于双因果键合图模型的定量故障隔离与参数估计方法。根据系统传感器配置方案,建立双因果键合图模型,通过因果路径分析,推导得到系统解析冗余关系,并获得故障特征矩阵。建立系统线性分式变换键合图模型,开展故障仿真,将其与双因果键合图模型耦合,在MATLAB/Simulink环境中进行仿真试验,实现了舰船主动力装置的故障隔离与参数估计。结果表明:对双因果键合图模型因果路径分析,可以避免手动推导系统解析冗余关系的繁杂过程;基于其部件构造方程的分析可以有效实现系统故障隔离与参数估计,实时跟踪和预测故障状态。

    Abstract:

    Aiming at the inherent characteristics of complicated structure, multiple fault types and system uncertainty of marine main power plant, a quantitative algorithm for fault isolation and parameter estimation based on bicausal BG (bond graph) was developed. Based on sensor configuration scheme, the system bicausal BG model was built. By analyzing the model causal path, the system ARRs (analytical redundancy relations) were derived and the fault signature matrix was obtained. The LFT (linear fractional transformation) BG model was developed for fault simulation. Through coupling LFT and bicausal BG models, the fault isolation and parameter estimation of marine main power plant were realized and the effectiveness was validated by MATLAB/Simulink software. Results show that the bicausalled BG helps to simplify ARRs deviation, and the fault isolation and parameter estimation can be effectively realized and the fault status can be tracked and predicted by analyzing the element constitutive equation of bicausalled BG.

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黄林,程刚,朱国情,等.舰船主动力装置故障隔离与参数估计方法. Fault isolation and parameter estimation of marine main power plant based on bicausal bond graphs[J].国防科技大学学报,2019,41(2):176-184.

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  • 收稿日期:2018-02-07
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  • 在线发布日期: 2019-04-24
  • 出版日期: 2019-04-28
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