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小型航空活塞发动机喷油异常的故障诊断
引用本文:沈峘,赵飞,毛建国,张晨,胡委.小型航空活塞发动机喷油异常的故障诊断[J].航空动力学报,2021,36(4):861-873.
作者姓名:沈峘  赵飞  毛建国  张晨  胡委
作者单位:1.南京航空航天大学 能源与动力学院,南京 210016
基金项目:航空科学基金(20170923001)
摘    要:针对小型航空活塞发动机出现的喷油异常故障,基于发动机的缸内压力和缸盖振动信号,采用一种变分模态分解和布谷鸟搜索优化支持向量机相结合的故障诊断方法对发动机喷油异常故障进行诊断。该方法使用变分模态分解对发动机的缸内压力信号和缸盖振动信号进行处理得到本征模态函数,对本征模态函数进行奇异值分解和能量特征提取,将缸内压力和缸盖振动的数据集输入布谷鸟搜索算法优化的支持向量机模型中进行训练和测试。结果表明:该方法较好地识别出发动机喷油异常的故障,其中缸内压力和缸盖振动信号的故障识别分类准确率分别为95.32%和92.47%,验证了该方法的有效性。 

关 键 词:故障诊断    航空活塞发动机    变分模态分解    布谷鸟搜索    支持向量机
收稿时间:2020/7/23 0:00:00

Fault diagnosis of abnormal fuel injection of small aviation piston engine
SHEN Huan,ZHAO Fei,MAO Jianguo,ZHANG Chen,HU Wei.Fault diagnosis of abnormal fuel injection of small aviation piston engine[J].Journal of Aerospace Power,2021,36(4):861-873.
Authors:SHEN Huan  ZHAO Fei  MAO Jianguo  ZHANG Chen  HU Wei
Institution:1.College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China2.Command and Control Communication Center,Shanghai Aerospace Electronic Technology Institute,Shanghai 201108,China
Abstract:Considering the abnormal fuel injection failure of small aviation piston engines, based on the engine’s in-cylinder pressure and cylinder head vibration signal, a fault diagnosis method combining variational modal decomposition and cuckoo search optimization support vector machine was used to diagnose abnormal fuel injection failure of the engine. The method used variational mode decomposition to process the in-cylinder pressure signal and cylinder head vibration signal of the engine to obtain an intrinsic mode function, perform singular value decomposition and energy feature extraction on the intrinsic mode function, and the data sets of in-cylinder pressure and cylinder head vibration were input into the support vector machine optimized by the cuckoo search algorithm for training and testing. Results showed that this method can better identify the faults of abnormal fuel injection of the engine, and the accuracy of the fault recognition classification of the pressure in the cylinder and the vibration signal of the cylinder head was 95.32% and 92.47%, respectively, verifying the effectiveness of the method. 
Keywords:fault diagnosis  aviation piston engines  variational mode decomposition  cuckoo search  support vector machine
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