局部缺陷滚动轴承系统多事件激励振动响应机理与识别方法的研究

The operating condition of rolling element bearing is very important for the precision, reliability and life of the machinery. Mechanism of the vibration response induced by rolling element bearing with local defect is key and fundamental scientific problem to accurately identify the healthy condition of the bearing. Considering the influence factors such as centrifugal force,gyroscopic moment, elastohydrodynamic lubrication and sliding etc., the nonlinear dynamics equation of roller element passing the local defect in the ring is established under the time-varying stiffness and displacement. The physical mechanism of vibration response signal inspired the local defect is investigated. The differences of contact condition in defect area during speed or overloaded variations are analyzed. The trend of informative frequency band in local damage is also studied. Combining the order tracking based on nonlinear chirplet wavelet transform, SK, and MED, the dual-impulse signal is enhanced and extracted. The new estimation method of defect size is proposed. The stress in the spalling region are analyzed under the impact load induced by rolling elements. Based on the theory of Weibull distribution and FEM dynamics, the stress, location and volume of spalling every time are determined. The model of defect evolution would be built. By EEMD, SVD and Mahalanobis-Taguchi system, the model is built to detect the incipient fault and distinguish degradation condition of bearings life. These models are revised and verified by theoretical analysis, simulation and experiment results. The research achievements in this project would provide solid foundation to establish a more reliable health management system of rolling element bearing.

滚动轴承运行状态对设备精度、可靠性和寿命都有重要影响，局部缺陷诱发的振动响应机理研究是准确地识别轴承健康状态的基础性关键科学问题。本项目拟考虑离心力、陀螺力矩、弹流润滑、滑动等影响因素，在时变刚度和时变位移下，建立滚动体通过局部缺陷时轴承系统的多事件激励的非线性动力学方程，研究局部缺陷诱发振动响应信号的物理机理，分析变速和变载荷时缺陷区域接触状态的差异，揭示缺陷损伤信息敏感频带随之变化的规律。采用非线性调频小波阶次跟踪、SK和MED等方法，增强和提取双脉冲响应信号，提出定量识别缺陷尺寸的新方法。基于Weibull分布和FEM动力学，研究在冲击载荷作用下，剥落区域等效应力、剥落位置、体积等参数，建立缺陷自然演化模型。基于EEMD、SVD和马田系统，建立识别早期故障时间点和区分性能退化阶段的模型。通过理论分析、仿真和实验对比，验证建立模型的正确性，研究成果将为建立轴承健康管理系统提供基础支撑。

本项目主要从正问题和逆问题两个方面研究了滚动轴承局部故障诱发振动的机理、故障识别和剩余寿命预测中关键性问题。针对局部缺陷轴承诱发的振动响应问题，分别建立了2自由度滚动轴承局部缺陷多事件模型、4自由度内/外圈单点复合故障模型、4自由度内/外圈多点复合故障模型、5自由度等温/热弹流润滑下内/外圈局部缺陷故障模型、基于能量法的轴承-转子-轴承座系统动力学模型，基于有限元法模拟滚动体经过局部缺陷时的接触应力场的变化和动态响应特性，系统地研究了各种局部缺陷轴承引起的振动响应；针对滚动轴承早期故障识别问题，提出了改进VMD-FRFT优化中心频率方法，以及回溯追踪、改进VMD和Infogram综合方方法，基于双脉冲特征的滚动轴承缺陷尺寸估计方法，提高早期故障识别精度；针对复合故障识别问题，提出了一种融合Autogram的共振解调和1.5维谱的滚动轴承复合故障诊断方法，在不分离信号的情况下，可以识别多种复合故障；针对轴承健康状态监测，构建了基于包络谱多特征的RMS-CUMSUM和 GRRMD-CUMSUM、多分数阶谱特征的MEMD-MFDFA和多域特征的CUMSUM马氏距离等状态监测指标，更容易对轴承健康状态的阶段划分，提出了基于风险评估和实时退化状态的滚动轴承剩余寿命预测方法。这些研究工作对于滚动轴承的故障诊断和预测提供了一些理论和方法，对工业设备的健康监测系统的设计具有一定的指导价值。.在本项目的资助下，项目团队在ISA Transactions、Structural Health Monitoring、IEEE Transactions on Instrumentation and Measurement、Measurement Science and Technology和《振动工程学报》等国内外期刊上发表和被录用了论文17篇，其中SCI检索论文10篇，EI检索论文4篇。登记软件著作权2项。培养毕业的硕士研究生13名，在读博士研究生3名，在读硕士研究生3名。

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