【摘要】 提出一种基于免疫学原理的免疫检测器生成算法,通过对故障信号(即有害抗原)的免疫疫苗、免疫学习和免疫应答进行故障模式识别和诊断,利用k-nearest neighbor分类法确定该模式的故障类型,该算法有较好的动态性、自适应性。把各代抗体集合作为随机序列,给出序列的收敛条件及证明,证明了所提出的算法是概率1收敛,并通过机组试验验证了由该算法产生的检测器对故障检测的有效性。更多还原

【Abstract】 A novel algorithm which generates immune detectors is proposed.Passing immune vaccine,immune learning and immune response of fault signal,fault pattern is identified and diagnosed.The algorithm uses of k-nearest neighbor classification method to decide fault type and has a good dynamic adaptive behavior.Regarding the set of each era antibodies mutated in the system learning as a random sequence,the condition of convergence of the series and a proof are presented.The algorithm’s astringency is proved.The machine unit experimental results show that the method is effective.更多还原