免疫编程的故障特征构造方法

在原始特征的多项式组合优化中,针对遗传编程易陷入局部优化解的缺点,引入了免疫编程的故障诊断优化策略,将类内类间散布矩阵判据作为抗体的亲和度,利用克隆、变异和更新等免疫算子实现抗体的优化,从而获得了最佳分类能力的复合特征.对发动机异响信号的6个典型时域特征的应用表明,克隆选择机制维持了抗体群体的多样性,同遗传编程方法相比,优化的复合特征具有更好的识别效果.

Features Generation in Fault Diagnosis Based on Immune Programming

Aiming at the shortage of premature convergence in the conventional genetic programming,a new feature generation method based on immune programming is put forward,where the new features are constructed by polynomial expressions of the original features,and the antibody affinity is defined by the ratio of inter-class scatter to the intra-class scatter.Combining cloning,hypermutation and replacement operator,the clonal selection optimal algorithm is adopted to search the best feature with excellent classification performance.The experiment of the six time domain features for engine sound signal shows that due to the maintained diversity of antibodies based on the clonal selection principle,the best compound feature constructed by immune programming is endowed with the better classification ability than the feature optimized by genetic programming.