摘要
在实际工程中,齿轮箱故障往往以复合故障的形式出现,不同故障的信号相互耦合,彼此干扰,难以进行准确诊断。采用变分模态分解(VMD)和最大相关峭度解卷积(MCKD)相结合的齿轮箱复合故障诊断方法,首先对齿轮箱复合故障进行变分模态分解,并根据互相关准则滤除噪声干扰;然后选取最佳的解卷积周期和滤波器长度,对降噪信号进行MCKD滤波,分离故障特征;最后将该方法应用于齿轮箱,实现其复合故障诊断。通过某油田作业区的现场应用,轴承和齿轮的故障特征频率凸显,证明了该方法的有效性。
In practical engineering,gearbox faults usually appear in the form of compound fault.The signals of different faults are coupled and interfered with each other,so it is difficult to diagnose the faults accurately.A method of gearbox compound fault diagnosis is proposed,which is based on the combination of variational mode decomposition(VMD)and maximum correlation kurtosis deconvolution(MCKD).Firstly,the compound faults of gearbox are decomposed into different modes,and the noise interference is filtered out according to the cross-correlation criterion.Then,the best deconvolution period and filter length are selected to filter the noise reduction signal with MCKD and separate the fault features.Finally,the method is applied to the gearbox to diagnose compound faults.Through the field application of one oilfield operation area,the fault characteristic frequency of bearings and gears are obvious,which proves the validation of the method.
作者
丛蕾
CONG Lei(Bazhou Branch of Daqing Oilfield Engineering Co.Ltd.)
出处
《油气田地面工程》
2020年第8期104-107,共4页
Oil-Gas Field Surface Engineering
关键词
齿轮箱
复合故障
变分模态分解
最大相关峭度解卷积
特征分离
故障诊断
gearbox
compound faults
variational mode decomposition
maximum correlation kurtosis deconvolution
feature separation
fault diagnosis