基于解析冗余关系理论的电力电子电路健康预测

讨论了电力电子电路中元器件级的健康预测。元器件级的剩余使用寿命是通过反推残差信号方法得到的。首先利用键合图建立系统的动态模型,得到全局解析冗余关系,通过故障特征矩阵进行故障检测与隔离;然后与元器件的退化模型相结合的方法,得到元器件相对应的残差退化曲线,从而获得元器件退化过程数据样本。根据元器件的等效电阻与残差的退化关系,结合故障阈值与失效值和极限学习机(extreme learning machine,ELM)算法可计算出元器件级的剩余使用时间。最后将该方法应用于典型电力电子电路Buck电路中,在20-sim软件和Matlab仿真环境中进行联合仿真,验证了此方法的有效性。

Research on Health Prediction of Power Electronic Circuit Based on Analytical Redundancy Relations Theory

This paper discusses the health prediction of component level in dynamic system. The residual service life of the component level is obtained by means of inverse residual signal. Firstly, the dynamic model of the system is established by using the bond graph, and the global analytical redundancy is obtained, and the fault detection and isolation is carried out by fault feature matrix. Then, the residual degradation curve corresponding to the components is obtained by combining the degradation mechanism of the components, so as to obtain the data samples of the degradation process of the components. According to the relationship between the equivalent resistance and residual degradation of components, the remaining use time of component level can be calculated by combining the fault threshold with the failure value and the Extreme Learning Machine (ELM) algorithm. Finally, this method is applied to the typical power electronic circuit Buck circuit, and the simulation is carried out in the 20-sim software and Matlab simulation environment to verify the effectiveness of this method.