Time-frequency representation based on robust local mean decomposition for multicomponent AM-FM signal analysis. (October 2017) - Liu, Zhiliang; Jin, Yaqiang; Zuo, Ming J.; Feng, Zhipeng
Highlights: A new improvement scheme of local mean decomposition is proposed to eliminate the end effect and mode mixing problems. The improved LMD is applied to time-frequency representation for multi-component AM-FM signals. The improved LMD in conjunction with the fast Kurtogram is applied to bearing fault diagnosis. Abstract: Local mean decomposition (LMD) is a promising approach to implement time-frequency representation (TFR) for multicomponent amplitude-modulated (AM) and frequency-modulated (FM) signal analysis; however, its performance usually suffers from end effect and mode mixing problems. To address this issue, this paper proposes a novel comprehensive scheme to improve LMD performance. The novel scheme can automatically determine the fix subset size of the moving average algorithm and the optimal number of sifting iterations in a sifting process. Extensive simulations have been explored for multicomponent AM-FM signal analysis by means of TFR with the improved LMD. Moreover, the improved LMD shows potential application in bearing fault diagnosis in conjunction with the well-known fast kurtogram.