基于IGA算法的航空发动机故障检测技术分析  

Analysis of Aircraft Engine Fault Detection Technology Based on IGA Algorithm

作　　者：高浩 岳晨旭 Gao Hao;Yue Chenxu(Unit 93137,Beijingg 100000,China)

机构地区：[1]93137部队,北京100000

出　　处：《机械管理开发》2025年第2期96-97,100,共3页Mechanical Management and Development

摘　　要：面对航空发动机故障诊断耗时长、诊断效果差的问题,基于免疫遗传算法(ImmuneGenetic Algorithm,IGA),提出一种智能化的航空发动机故障检测技术。其中首先采用因果与概率关系来构建发动机故障问题模型,其次采用IGA模型进行故障问题求解,最后以某A航空发动机进行实验分析。与同类技术相比,IGA模型故障检测耗时最短为15.8s。而在故障检测效果分析中,IGA模型检测效果最好,最接近实际机械故障征兆系数值,故障检测准确率为97.25%,同类技术中表现最好。最后,根据实验结果表明该航空发动机主要故障为滑油导管振裂与传动轴折断。由此可见,研究模型具有良好应用效果,研究内容将为航空发动机高效故障检测以及故障维护提供技术支持。Facing the problems of long time-consuming and poor diagnosis of aero-engine fault diagnosis,the study proposes an intelligent aero-engine fault detection technology based on ImmuneGeneticAlgorithm(IGA).Among them,the study adopts the causal and probabilistic relationship to construct the engine fault problem model,followed by the IGA model to solve the fault problem,and finally the experimental analysis is carried out with a certain Aero-engine.Compared with similar techniques,the IGA model has the shortest fault detection time of 15.8 s.In the analysis of fault detection effect,the IGA model has the best detection effect,which is the closest to the actual mechanical failure sign coefficient value,and the fault detection accuracy rate is 97.25%,which is the best performance among similar techniques.Finally,according to the experimental results,the main faults of the aero-engine are the cracking of the sliding oil conduit and the fracture of the drive shaft.This shows that the research model has good application effect,and the research content will provide technical support for the efficient fault detection and fault maintenance of the aero-engine.

关 键 词：IGA 航空发动机 故障检测 因果关系 概率 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]