A hybrid filtering method based on a novel empirical mode decomposition for friction signals

作者：Li Chengwei; Zhan Liwei

来源：Measurement Science and Technology, 2015, 26(12): 125003.

DOI：10.1088/0957-0233/26/12/125003

• empirical mode decomposition
• signal filtering
• modified Hausdorff distance
• friction signal

During a measurement, the measured signal usually contains noise. To remove the noise and preserve the important feature of the signal, we introduce a hybrid filtering method that uses a new intrinsic mode NIMF) and a modified Hausdorff distance. The NIMF is defined as the difference between the noisy signal and each intrinsic mode IMF), which is obtained by empirical mode decomposition (EMD), ensemble EMD, complementary ensemble EMD, or complete ensemble EMD with adaptive noise (CEEMDAN). The relevant mode selecting is based on the similarity between the first NIMF and the rest of the NIMFs. With this filtering method, the EMD and improved versions are used to filter the simulation and friction signals. The friction signal between an airplane tire and the runaway is recorded during a simulated airplane touchdown and features spikes of various amplitudes and noise. The filtering effectiveness of the four hybrid filtering methods are compared and discussed. The results show that the filtering method based on CEEMDAN outperforms other signal filtering methods.

• 出版日期2015-12
• 单位哈尔滨工业大学