Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis
Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis
复制标题
基于集合经验模态分解和自零空间投影分析的转子轴承系统故障识别
DOI：
10.1016/j.jsv.2014.03.014
复制
发表时间：
2014-07-07
影响因子：
4.7
通讯作者：
Chen, Guoan
中科院分区：
文献类型：
--
作者：
Jiang, Fan;Zhu, Zhencai;Chen, Guoan
转子-轴承系统的振动信号具有非线性和非平稳性，通过分析信号来准确识别故障是一项具有挑战性的工作。针对这一问题，提出了一种基于集成经验模式分解(EEMD)和自零空间投影分析的新方法。这种方法寻求使用简单的代数计算和投影分析来识别转子-轴承系统中出现的故障。首先，利用EEMD将采集到的振动信号分解成一组固有模式函数(IMF)进行特征提取。其次，利用提取的各种机械健康状态下的特征，根据空间投影分析设计自零空间矩阵。最后，计算所谓的投影指标，用简单的推理逻辑识别转子-轴承系统的故障。通过实验验证了该方法的可靠性和有效性。结果表明，该方法能够准确识别转子-轴承系统的故障。(C)2014爱思唯尔有限公司。保留所有权利。
Accurately identifying faults in rotor-bearing systems by analyzing vibration signals, which are nonlinear and nonstationary, is challenging. To address this issue, a new approach based on ensemble empirical mode decomposition (EEMD) and self-zero space projection analysis is proposed in this paper. This method seeks to identify faults appearing in a rotor-bearing system using simple algebraic calculations and projection analyses. First, EEMD is applied to decompose the collected vibration signals into a set of intrinsic mode functions (IMFs) for features. Second, these extracted features under various mechanical health conditions are used to design a self-zero space matrix according to space projection analysis. Finally, the so-called projection indicators are calculated to identify the rotor-bearing system's faults with simple derision logic. Experiments are implemented to test the reliability and effectiveness of the proposed approach. The results show that this approach can accurately identify faults in rotor-bearing systems. (C) 2014 Elsevier Ltd. All rights reserved.