Bearing fault diagnosis under unknown variable speed via gear noise cancellation and rotational order sideband identification
Bearing fault diagnosis under unknown variable speed via gear noise cancellation and rotational order sideband identification
复制标题
通过齿轮噪声消除和旋转阶次边带识别进行未知变速下的轴承故障诊断
DOI：
10.1016/j.ymssp.2015.03.005
复制
发表时间：
2015-10
影响因子：
8.4
通讯作者：
Li, Chuan
中科院分区：
文献类型：
--
作者：
Liang, Ming;Li, Jianyong;Cheng, Weidong;Li, Chuan
齿轮箱的干扰振动信号通常代表了滚动轴承故障检测和诊断的一个具有挑战性的问题，特别是在未知的变速条件下。虽然已经提出了一些方法来消除齿轮箱干扰信号的离散频率的基础上，这些方法可能无法很好地工作在未知的变速条件。因此，我们提出了一种新的方法来解决这个问题。该方法包括三个主要步骤：（a）自适应齿轮干涉消除，（B）基于故障特征阶数（FCO）的故障检测，（c）基于旋转阶数边带（ROS）的故障类型识别。针对齿轮干涉消除问题，提出了一种增强型自适应噪声消除算法。新的ANC算法不需要额外的加速度计来提供参考输入。相反，参考信号自适应地从信号最大值和瞬时主网格多重（IIMM）趋势构造。关键ANC参数，如滤波器长度和步长也被定制，以适应变速条件下，使用ROS故障类型诊断的主要优点是，它是不易混淆的轴承和齿轮旋转频率的峰值共存的轴承故障特征频率的识别中的FCO子阶区域。所提出的方法的有效性已被证明使用仿真和实验数据。我们的实验研究还表明，所提出的方法是适用的，无论轴承和齿轮转速是否成比例的对方。
The interfering vibration signals of a gearbox often represent a challenging issue in rolling bearing fault detection and diagnosis, particularly under unknown variable rotational speed conditions. Though some methods have been proposed to remove the gearbox interfering signals based on their discrete frequency nature, such methods may not work well under unknown variable speed conditions. As such, we propose a new approach to address this issue. The new approach consists of three main steps: (a) adaptive gear interference removal, (b) fault characteristic order (FCO) based fault detection, and (c) rotational-order-sideband (ROS) based fault type identification. For gear interference removal, an enhanced adaptive noise cancellation (ANC) algorithm has been developed in this study. The new ANC algorithm does not require an additional accelerometer to provide reference input. Instead, the reference signal is adaptively constructed from signal maxima and instantaneous dominant meshing multiple (IDMM) trend. Key ANC parameters such as filter length and step size have also been tailored to suit the variable speed conditions, The main advantage of using ROS for fault type diagnosis is that it is insusceptible to confusion caused by the co-existence of bearing and gear rotational frequency peaks in the identification of the bearing fault characteristic frequency in the FCO sub-order region. The effectiveness of the proposed method has been demonstrated using both simulation and experimental data. Our experimental study also indicates that the proposed method is applicable regardless whether the bearing and gear rotational speeds are proportional to each other or not.
登录
查看更多内容
DOI：
10.20381/ruor-18797
发表时间：
2008
期刊：
--
影响因子：
--
作者：
Raymond Wang
通讯作者：
Raymond Wang
影响因子：
20.6
作者：
WIDROW, B;GLOVER, JR;GOODLIN, RC
通讯作者：
GOODLIN, RC
影响因子：
1.1
作者：
W. Wang
通讯作者：
W. Wang
通过故障特征阶次 (FCO) 分析进行滚动轴承故障诊断
影响因子：
8.4
作者：
Wang, Tianyang;Liang, Ming;Cheng, Weidong
通讯作者：
Cheng, Weidong
影响因子：
8.4
作者：
MCFADDEN, PD
通讯作者：
MCFADDEN, PD