Online Rotor Systems Condition Monitoring Using Nonlinear Output Frequency Response Functions Under Harmonic Excitations
Online Rotor Systems Condition Monitoring Using Nonlinear Output Frequency Response Functions Under Harmonic Excitations
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DOI：
10.1109/tii.2022.3141866
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发表时间：
2022-10-01
影响因子：
12.3
通讯作者：
Liu, Yang
中科院分区：
文献类型：
--
作者：
Zhu, Yun-Peng;Zhao, Yu-Lai;Liu, Yang
转子系统的碰摩和不对中等运行工况通常会累积起来，最终导致严重的故障。这些异常情况往往使转子系统的行为非线性。因此，非线性信号和系统分析已被应用于解决转子系统的状态监测和故障诊断问题。非线性频率响应函数（Nonlinear Frequency Response Function，NOFRFs）是将频率响应函数的概念扩展到非线性情况的一种新概念，近年来被用于解决基于信号分析的转子系统状态监测和故障诊断问题。然而，现有的基于NOFRF的分析需要对转子系统进行离线实验。这不能满足工业上对转子系统运行状态进行连续监测的需要，而这对于在线故障诊断是非常重要的。为了解决这个问题，本文提出了一种新的方法，执行转子系统的状态监测使用的NOFRF直接从转子系统的在线运行数据，这是固有的谐波确定。该方法涉及从谐波激励和相应响应识别转子系统的数据驱动NARX（具有eXegenous输入的非线性自回归）模型，使用识别的NARX模型评估转子系统NOFRFs，以及使用评估的NOFRFs进行转子系统运行状态监测和故障诊断。该方法，第一次，使NOFRF被应用于转子系统的在线监测。实验研究已经进行，以验证所提出的方法的有效性和潜在的应用，以及它的优势，常用的信号分析为基础的技术。
Operation conditions such as rub-impact and misalignment usually accumulate and can eventually induce severe faults in rotor systems. These abnormal conditions often make rotor systems behave nonlinearly. Consequently, nonlinear signal and systems analyses have been applied to address rotor system condition monitoring and fault diagnosis problems. Nonlinear frequency response functions (NOFRFs) are a concept proposed to extend the well-known concept of frequency response function to the nonlinear case, and have recently been exploited to solve problems with signal analysis based rotor system condition monitoring and fault diagnosis. However, existing NOFRFs based analyses require conducting offline experiments on rotor systems. This cannot satisfy the industrial need of continuous monitoring of rotor system operational conditions, which is important for online fault diagnosis. In order to resolve this problem, the present article proposes a novel approach that performs the rotor system condition monitoring using the NOFRFs determined directly from the rotor system online operational data which are inherently harmonics. This approach involves the identification of a data-driven NARX (nonlinear auto regressive with eXegenous input) model of rotor systems from harmonic excitations and corresponding responses, evaluation of rotor system NOFRFs using the identified NARX model, and the use of evaluated NOFRFs for rotor system operational condition monitoring and fault diagnosis. The approach, for the first time, enables the NOFRFs to be applied to perform online monitoring of rotor systems. Experimental studies have been conducted to verify the effectiveness and potential applications of the proposed approach as well as its advantages over commonly used signal analysis based techniques.