活塞-缸套摩擦副状态表征参数选取方法研究OA北大核心CSTPCD
Research on the Selection Method of State Characterization Parameters of Piston-Cylinder Liner Friction Pairs
建立柴油机试验台架采集数据,对机体表面振动信号进行时频分析,探明不同激励源与机体表面振动信号的关系.选取变分模态分解(variational mode decomposition,VMD)算法对振动信号进行分解,提取各分量的表征参数.通过探究转矩、转速、润滑油温度及配缸间隙与各表征参数的相关性,初步确定相关性强的表征参数集.通过多评价准则对上述表征参数集进行分析,最终得出贡献度最高的表征参数为本征模态函数(intrinsic mode function,IMF)1 的标准差、均方频率、峭度、最大奇异值、频域积分和 IMF6 的脉冲因子、标准差、重心频率、频率方差及最大奇异值.
The diesel engine test bench was set up to collect data,and time-frequency analysis was conducted to determine the correlation between various excitation sources and the vibration signals on the body surface.Variational mode decomposition algorithm was utilized to decompose the vibration signal and extract the characterization parameters of each component.By examining the relationship between torque,rotational speed,lubricating oil temperature,and cylinder clearance with each characterization parameter,the characterization parameter set with a strong correlation was preliminarily determined.The set of characterization parameters mentioned above were analyzed by using multiple evaluation criteria.After analysis,it is determined that the characterization parameters with the highest contribution are the standard deviation,mean square frequency,kurtosis,maximum singular value,and frequency-domain integral of IMF1 and the pulse factor,standard deviation,center of gravity frequency,frequency variance,and maximum singular value of IMF6.
魏敬宏;纪少波;胡珑渝;张珂;张志鹏;姜颖
山东大学 能源与动力工程学院,济南 250100
能源与动力
活塞-缸套故障诊断表征参数提取连续小波变换信号分解算法多评价准则
piston-cylinder linerfault diagnosischaracterization parameter extractioncontinuous wavelet transformsignal decomposition algorithmmultiple evaluation criteria
《内燃机工程》 2024 (002)
75-84 / 10
评论