方位(导航)
断层(地质)
特征(语言学)
材料科学
模式识别(心理学)
计算机科学
人工智能
地质学
地震学
语言学
哲学
作者
Xueping Ren,L. B. Guo,Tongtong Liu,Chao Zhang,Zhen Pang
标识
DOI:10.1088/1361-6501/ad7a96
摘要
Abstract The defects-induced periodic pulse is one of the important indices for the characterization of bearing failure. To solve the problem that the weak impact features caused by the early fault of the rolling bearing are easily to be interfered with by noise and strong background signal and are difficult to extract, an improved morphological filtering method combined with the Teager energy operator (IMF-TEO) is proposed to extract weak shock features. Firstly, according to the correlation between the periodic pulse induced by defects and the Morlet wavelet, the Morlet wavelet is used as the model to construct the structural elements. Then, capturing the Pearson correlation coefficient of the structural elements and the original signal and the signal is filtered by the variable scale morphological filter after threshold screening. Finally, the TEO is used as the post-enhancement link to suppress the noise in the signal after morphological processing and further highlight the fault characteristics. Simulation signals, experimental signals, and field signals verify the effectiveness and robustness of the proposed method.
科研通智能强力驱动
Strongly Powered by AbleSci AI