摘要
气门是柴油机中主要的零部件,对其进排气门间隙故障进行诊断研究具有重要的工程意义.文中采用变分模态和奇异值分解相结合的方法对其进行故障诊断.对柴油机振动信号进行变分模态分解,对变分模态分量进行奇异值分解,提取奇异值特征向量,用模糊C均值聚类方法对故障种类进行识别,并进行了试验验证.研究结果表明,与基于经验模态分解和奇异值分解相结合的方法相比,该方法能够更加准确有效地对不同的气门间隙异常故障进行识别,具有更高的诊断精度.
The valve is the main component in the diesel engine, and it is of great engineering significance to diagnose and study the intake and exhaust valve clearance faults. In this paper, the method of combining variational mode decomposition and singular value decomposition was utilized to identify the diesel engine valve clearance faults. The vibration signal of diesel engine was decomposed by variational mode and the component of variational mode was decomposed by singular value. Then the singular value feature vector was extracted, and the fault types were identified by fuzzy C-means clustering method, which is verified by experiments.The results show that compared with the method based on the combination of empirical mode decomposition and singular value decomposition, the proposed method can identify different abnormal valve clearance faults more accurately and effectively with higher diagnostic accuracy.
作者
高清春
胡甫才
GAO Qingchun;HU Fucai(Key Laboratory of High Performance Ship Technology,Wuhan University of Technology,Ministry of Education,Wuhan 430063,China;School of Energy and Power Engineering,Wuhan University of Technology,Wuhan 430063,China)
出处
《武汉理工大学学报（交通科学与工程版）》
2019年第4期746-751,共6页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家纵向项目高技术船舶专项资助(20121g0023)
关键词
柴油机
变分模态分解
奇异值分解
气门间隙
diesel engine
variational mode decomposition
singular valuedecomposition
valve clearance
