稳健性(进化)
拉马努詹之和
傅里叶变换
断层(地质)
噪音(视频)
计算机科学
希尔伯特-黄变换
控制理论(社会学)
算法
工程类
人工智能
数学
白噪声
数学分析
地质学
电信
生物化学
化学
控制(管理)
组合数学
地震学
图像(数学)
基因
作者
Jian Cheng,Yu Yang,Zhantao Wu,Haidong Shao,Haiyang Pan,Junsheng Cheng
标识
DOI:10.1109/tii.2021.3132334
摘要
As an important part of rotating machinery, gear is easy to appear some unexpected fault states, and its fault diagnosis is very important. Fourier decomposition method (FDM) is a common method for gear fault diagnosis, but the noise robustness, period recognition, and extraction capabilities of FDM are unsatisfactory. Based on this, in this article, Ramanujan Fourier mode decomposition (RFMD) method is proposed. The RFMD not only has a complete mathematical theory foundation but also has an excellent ability to identify and extract periodic components. Emulational and experimental results of planetary gearbox show that the RFMD method has good noise robustness and can accurately extract gear fault characteristic information. Thus, it is an effective gear fault diagnosis method.
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