可拓否定选择算法及其在故障诊断中的应用

A new negative selection algorithm based on Extenics and its application in fault diagnosis

针对传统故障诊断算法无法利用正常状态样本实现故障检测的问题,将可拓学与否定选择算法相融合,提出一种可拓否定选择算法。采用基元对模型进行描述,根据关联函数定义亲和度的计算公式,并分别设计可拓检测器的生成和优化算法,在可拓检测器生成阶段,通过对初始检测器进行自体耐受得到成熟检测器;在可拓检测器优化阶段,通过对成熟检测器进行合并得到数目更少的成熟检测器;在参数分析中讨论了亲和度阈值对检测器覆盖率和检测率的影响。最终采用可拓否定选择算法对某型飞机综合显控平台的测试数据进行故障检测,得到的成熟检测器不仅个数少、无冗余,而且具有较高的检测率,结果表明该算法能够解决无故障样本条件下的故障检测问题,且检测结果与实际情况相符。

In this paper, the extension negative selection algorithm is proposed by fusing Extenics and negative selec？tion algorithm, aiming at the problem that traditional diagnosis algorithm can hardly solve fault detection by using nor？mal state data. The basic elements are adopted to describe the models of problem domain, detectors and training sam？ples, the dependent function is used to define the affinity calculation formula, and the extension detector generation and optimization algorithm are designed. In the phase of extension detector generation, the mature detectors are taken through the self？tolerance and in the phase of extension detector optimization, less mature detectors are taken through merging the detectors. The influence of threshold value of the degree of affinity on the coverage rate and detection rate of detectors are discussed in the parameter analysis. Finally, the proposed algorithm is used for fault detection of an integrated display and control platform. The obtained mature detectors not only have less numbers and are non？redun？dant, but also have high detection rate. The results showed that the algorithm can solve the fault detection problem in the condition of no fault state data and the detection results are consistent with the practive.