关键词：角域特征量；小波滤波；样条插值；振源识别
中图分类号：TH17 文献标识码：A
Vibration Resource Identification of Multi Low Speed, High- loaded Bearings Installed on Same Axis based on Characteristic of Corner - domain
Han Jia-hua， Yan Wen， Cao Jin-Hua
(Mechanical Engineering College，Shijiazhuang 050003， China)
Abstract：Multi Low Speed, High- loaded Bearing Installed on Same Axis, different locations of the bearing fault pulse will appear aliasing coupling phenomenon, resulting in fault signal vibration source identification difficult. In this regard, based on the angular signal, the concept of part contact angle is proposed, and the fault signal source identification is carried out. By using the Haar wavelet function to transform the displacement signal, the spline interpolation algorithm is used to transform the acquired time domain nonstationary signal into the angular pseudo-stationary signal to realize the angular area resampling, extract the angular feature quantity, and make the vibration source recognition.To solve the multi-bearing coaxial installation of the fault signal superposition problem. Through the experimental analysis, the results show that the method based on the angular feature quantity can meet the requirements of vibration signal identification of fault signal to a certain extent, and it has certain practicability.
Key words: characteristic of corner-domain; wavelet filtering; spline interpolation; vibration resource identification
低速重载轴承是大型机械设备的核心部件之一，其运行状况直接影响整台设备的性能。机械设备运转过程中，转速变化、负载大小、不同类型的故障产生的冲击都会导致轴承的振动信号具有非平稳性。如何分析轴承故障信号的特点，提取反映故障问题的特征参量，进行轴承故障诊断具有一定的现实意义。
近年来，随着机械故障诊断理论研究的不断深入，提出了一系列故障诊断方法[1-4]：经验模态分解，局部均值分解，自相关分析，阶次跟踪分析等。这些方法在进行故障特征信息融合，提取轴承故障信号特征，进行轴承故障诊断方面取得了良好的效果。但是，多个低速重载轴承同轴安装时，产生的故障信号特点，上述故障诊断方法的诊断效果不是很明显。针对此类轴承工作时的故障信号特点，提出了基于角域特征量的故障信号振源识别方法。
1 多轴承安装时故障信号特点
作为大型工程部件，低速重载轴承常运用于诸如起重机、采煤机和转炉等大型机械装置中。此类轴承具有低速、重载、往复运动、载荷作用方向变化复杂的特点[5-6]，其结构和工作特点决定相应轴承故障振动信号具有以下特点：
（1）故障频率低。低速重载轴承由于工作转速低，承受载荷大，产生故障信号的故障频率常处于零点几赫兹到几赫兹之间；
（2）故障类型多。低速重载轴承故障
类型主要是内圈、外圈、滚动体、保持架四种故障类型，以及各部件故障严重程度的不同；
（3）故障信号混叠耦合现象。多轴承同轴安装，故障轴承为多个，不同振源产生的故障信号会相互影响，出现混叠耦合现象。
