A Walsh transform-based Teager energy operator demodulation method to detect faults in axial piston pumps
A Walsh transform-based Teager energy operator demodulation method to detect faults in axial piston pumps
复制标题
基于沃尔什变换的轴向柱塞泵故障检测Teager能量算子解调方法
DOI：
10.1016/j.measurement.2018.10.085
复制
发表时间：
2019-02
期刊：
影响因子：
5.6
通讯作者：
Jihong Pang
中科院分区：
文献类型：
--
作者：
Qiang Gao;Hesheng Tang;Jiawei Xiang;Yongteng Zhong;Shaogan Ye;Jihong Pang
振动信号携带了大量的信息，代表了轴向柱塞泵的健康状况。然而，在实际工作过程中，轴向柱塞泵的振动信号往往会被强背景噪声所污染。针对这一问题，提出了一种沃尔什变换去噪与Teager能量算子（TEO）解调相结合的方法。沃尔什变换尚未应用于信号去噪领域。本文提出的基于软阈值的沃尔什变换去噪方法结合了沃尔什变换和软阈值去噪算法的优点，能够快速、自适应地对原始信号进行去噪。由于TEO可以同时估计信号的动能和势能，因此与传统的Hilbert解调相比，基于TEO的解调将更适合于提取故障。仿真和实验结果验证了该方法的可行性。诊断结果表明，该方法能够有效、快速地识别轴向柱塞泵的故障。
Vibration signals carry a great deal of information that represents the health conditions of axial piston pumps. However, in the working conditions, the vibration signals of the axial piston pumps are often contaminated by the presence of heavy background noises. In order to solve the problem, a hybrid method of Walsh transform denoising and Teager energy operator (TEO) demodulation is proposed. Walsh transform has not been applied to the field of signal denoising. The soft threshold-based Walsh transform denoising method proposed in the present study combines the advantages of Walsh transform and soft threshold denoising algorithm which can rapidly and adaptively de-noise raw signals. Since the TEO could estimate both of the kinetic and potential energy of a signal, a TEO-based demodulation would be more suitable to extract faults, when compared to the traditional Hilbert demodulation. Simulations and experimental investigations were implemented to illustrate the feasibility of the proposed method. These diagnostic results show that the proposed method enables the efficient and rapid recognition of axial piston pumps faults.
登录
查看更多内容
用于风力涡轮机叶片结构健康监测的碳纤维增强树脂复合材料层压板的定量损伤检测和稀疏传感器阵列优化
DOI：
10.3390/s140407312
发表时间：
2014-04-23
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Li X;Yang Z;Chen X
通讯作者：
Chen X
预测轴向柱塞泵滑靴副热弹流体动力润滑特性的新模型
影响因子：
7.3
作者：
汤何胜;任燕;向家伟
通讯作者：
向家伟
DOI：
10.1109/taslp.2017.2678684
发表时间：
2017-05-01
影响因子：
5.4
作者：
Shokouhi, Navid;Hansen, John H. L.
通讯作者：
Hansen, John H. L.
影响因子：
4.4
作者：
Hesheng Tang;Yaochen Yin;Yang Zhang;Jing Li
通讯作者：
Hesheng Tang;Yaochen Yin;Yang Zhang;Jing Li
基于非广延小波特征尺度熵和支持向量机的轴承运行状态识别
影响因子：
5.6
作者：
Dong, Shaojiang;Tang, Baoping;Chen, Renxiang
通讯作者：
Chen, Renxiang