球轴承疲劳剩余寿命分析与预测方法研究
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摘要
球轴承作为滚动轴承中的重要一类,广泛应用于各类机械产品中。作为易损件,球轴承也是机械产品的主要故障源之一,没有预知的球轴承失效不仅影响维修策略的制定,而且可能造成灾难性事故。因此,有效地预测球轴承的疲劳剩余寿命有助于了解机械产品健康状态并制定优化的维修策略。传统的球轴承疲劳寿命预测方法多是基于概率统计的总体寿命预测方法,而基于过程数据的疲劳寿命预测方法虽然可用于个体球轴承疲劳剩余寿命的预测,但是该方法主要依赖于球轴承的状态信息,缺乏对失效机理的研究,使得现有模型在预测球轴承疲劳剩余寿命时的准确性和可信度存在不足。
针对上述问题,本文在国家自然科学基金和部委级预研基金的资助下,以非线性动力学为基础研究球轴承缺陷生长机理,以改进的EMD方法作为球轴承性能退化特征量的提取手段,开展球轴承疲劳剩余寿命分析,并在缺陷微观失效模式检测分析的基础上,结合Paris疲劳剩余寿命预测理论,从失效机理出发研究个体球轴承的疲劳剩余寿命预测方法。论文主要研究内容如下:
1.针对含有表面缺陷的球轴承复杂的非线性动力学关系,以滚珠为对象建立球轴承非线性动力学方程,引入用于描述轴承内外圈相对侧倾状态的伴随方程,完整描述个体球轴承的非线性动力学问题。在此基础上,通过引入分段函数和缺陷冲击函数,建立单表面缺陷球轴承非线性动力学方程,并得到相应的缺陷冲击计算公式,用解析的方法描述单表面缺陷球轴承的动力学特性,为提出疲劳剩余寿命预测方法提供理论支撑。
2.为提高利用EMD方法提取球轴承性能退化特征量的准确性,针对EMD方法的端点效应和模态混淆等问题,分别采用镜像法和在模态混淆的IMFs中加入小幅均值为零的宽带白噪声后,再通过EMD进行分解的方法,解决端点效应和模态混淆的问题。在此基础上,结合EMD标准化过程,提出了改进的EMD方法,并用于提取球轴承性能退化特征量,利用灰色模型对球轴承性能退化特征量在疲劳剩余寿命预测中的应用进行了验证,结果表明:采用改进的EMD方法提取的性能退化特征量能有效地反映出球轴承的健康状态。
3.依据缺陷微观失效模式,结合临界面法,提出了临界曲面的概念,将球轴承疲劳裂纹扩展问题从三维转化为二维进行分析,使得传统的Paris理论可用于预测球轴承的疲劳剩余寿命。在此基础上,将球轴承疲劳失效过程分为裂纹扩展和剥落点尺寸增大两部分,基于临界曲面的概念提出了改进的Paris球轴承疲劳剩余寿命预测模型,通过6205深沟球轴承试验数据验证了该模型的有效性。
4.针对球轴承疲劳剩余寿命的在线预测问题,将振动信号数据分析与微观形貌检测相结合,提出球轴承疲劳剩余寿命在线预测模型。针对球轴承未出现异常信号时疲劳剩余寿命的预测问题,将历史疲劳寿命数据的统计特征量作为先验知识,以权重函数的方式引入预测模型中,实现对个体球轴承疲劳寿命和疲劳剩余寿命的在线预测,并通过试验验证了上述两种模型的有效性。
总之,本文基于非线性动力学深入分析球轴承缺陷的生长机理,通过改进的EMD方法提取球轴承性能退化特征量,并给出了疲劳寿命与缺陷生长过程之间的关系。在此基础上,充分利用球轴承宏观统计寿命特征,结合Paris理论可预测个体球轴承疲劳剩余寿命的特点,提出球轴承疲劳剩余寿命预测模型,实现个体球轴承疲劳剩余寿命的在线预测,对有效实施设备健康管理、故障诊断与视情维修具有重要的意义。
As an important category of rolling element bearing, ball bearing is widely used in mechineries. But as a vulnerable part, ball bearing is one of the primary sources of mechinery failure. The failure without precognition not only baffles the establishment of maintenance policy, but also may bring about catastrophic accidents. So the residual fatigue life prediction of ball bearing is helpful in cognizing the health of mechanics and optimizing the maintenance policy of mechanical system. Most traditional methods of residual fatigue life prediction of ball bearings are probability-based prognosis techniques which only can estimate the overall life of ball bearings. However, methods of data-driven prognosis can predict the life of a single ball bearing, but these methods are mainly dependent on state signals not faults themselves. So the accuracy and reliability of existing models are not competent when these models are used to predict the residual fatigue life of ball bearing.
In accordance with these problems, supported by the National Natural Science Foundation of China and the Ministerial-Level Pre-Research Fund, based on nonlinear dynamics of ball bearings as the basis of failure analysis, improved EMD method as the mean of fault feature extraction, the fatigue life of ball bearing is analyzed. Together with microscopy failure modes of faults, combined with the contributions of fatigue life prediction theory based on Paris, this paper is devoted to research the residual fatigue life prediction of single ball bearing in the origin of failure mechanism. The main contributions of this dissertation are summarized as follows:
1. Aiming at complex relationships in nonlinear dynamics of ball bearing with defects, nonlinear dynamic equations of ball bearing are established on the basis of balls as the objects and the adjoint equation which is used to describe the lean of inner ring to the outer ring is inducted. Together they can describe the dynamic characteristics of the single ball bearing perfectly. Then subsection functions and the defect impulse function are inducted and nonlinear dynamic equations of ball bearing with a single surface defect are proposed on the basis of proposed nonlinear dynamic equations of ball bearing and the impact energy equations are enduced. Then nonlinear dynamic characteristics of ball bearing with a single surface defect can be described by analytical methods and it provides a theoretical basis for investigating fatigue failure mechanism in depth.
2. In order to improve the accurance of performance degenerate values of ball bearings extracted by Empirical Mode Decomposition (EMD), aiming at problems of boundary effect and modal confusion of EMD, mirror method and adding a small broadband white noise with zero mean into Intrinsic Mode Functions (IMFs) with modal confusion and then decomposed by EMD again are used to solve these problems. On this basis, combining with the improved EMD standardization process, an improved EMD method to improve the accuracy of performance degenerate values of ball bearings is proposed. Finally, the improved EMD method is applied to extract the performance degenerate values of ball bearings, together with grey model, a residual fatigue life prediction model is proposed and is verified by historial data of 6205 deep groove ball bearing. Based on this, the application of performance degenerate values in residual fatigue life prediction is analyzed and it shows that the performance degenerate values extracted by improved EMD can describe the health of ball bearing.
3. According to micro-morphology of fatigue spalling, based on critical plane, the concept of critical surface is presented, then the three-dimensional crack propagation of ball bearings is transformed into two-dimensional and this enables the traditional method can be applied in them. Based on this, the fatigue life of ball bearings is divided into two parts: fatigue crack growth and fatigue spalling propagation. Then a residual fatigue life prediction model of ball bearing is proposed based on improved Paris law and its efficiency is verified by historical lives of 6205 deep groove ball bearings.
4. Aiming at residual fatigue life prediction of ball bearings on line, by combining data analysis of vibration signals with investigation of micro-morphology observation and analysis of fatigue spalling, the on-line prediction of residual fatigue life of ball bearing is proposed. Aiming at the life prediction in the phase before the appearance of detectable exceptional signals, history life data is treated as a prior knowledge and introduced into the proposed prediction model as a weighting function and then a prediction model which can predict the fatigue life and residual fatigue life of ball bearing on line is proposed. Then the validity of the model is verified by experimental data.
In summary, this paper launched the study on defect growth mechanism based on nonlinear dynamics theory of fault ball bearings and fault feature extraction by the improved EMD method. Based on this, the relationship between fatigue life and defect growth process is investigated. On the basis of this, utilizing the macroscopical statistics of fatigue life evaluated by traditional fatigue life prediction, combining with the advantage of Paris law which can predict the residual fatigue life of the single ball bearing, a residual fatigue life prediction model is proposed. The model can be used to predict the residual fatigue life and fatigue life of the single ball bearing on line. This fills the blank of on-line prediction methods of the single ball bearing and it is helpful for health management, failure diagnosis and condition-based maintainance.
针对上述问题,本文在国家自然科学基金和部委级预研基金的资助下,以非线性动力学为基础研究球轴承缺陷生长机理,以改进的EMD方法作为球轴承性能退化特征量的提取手段,开展球轴承疲劳剩余寿命分析,并在缺陷微观失效模式检测分析的基础上,结合Paris疲劳剩余寿命预测理论,从失效机理出发研究个体球轴承的疲劳剩余寿命预测方法。论文主要研究内容如下:
1.针对含有表面缺陷的球轴承复杂的非线性动力学关系,以滚珠为对象建立球轴承非线性动力学方程,引入用于描述轴承内外圈相对侧倾状态的伴随方程,完整描述个体球轴承的非线性动力学问题。在此基础上,通过引入分段函数和缺陷冲击函数,建立单表面缺陷球轴承非线性动力学方程,并得到相应的缺陷冲击计算公式,用解析的方法描述单表面缺陷球轴承的动力学特性,为提出疲劳剩余寿命预测方法提供理论支撑。
2.为提高利用EMD方法提取球轴承性能退化特征量的准确性,针对EMD方法的端点效应和模态混淆等问题,分别采用镜像法和在模态混淆的IMFs中加入小幅均值为零的宽带白噪声后,再通过EMD进行分解的方法,解决端点效应和模态混淆的问题。在此基础上,结合EMD标准化过程,提出了改进的EMD方法,并用于提取球轴承性能退化特征量,利用灰色模型对球轴承性能退化特征量在疲劳剩余寿命预测中的应用进行了验证,结果表明:采用改进的EMD方法提取的性能退化特征量能有效地反映出球轴承的健康状态。
3.依据缺陷微观失效模式,结合临界面法,提出了临界曲面的概念,将球轴承疲劳裂纹扩展问题从三维转化为二维进行分析,使得传统的Paris理论可用于预测球轴承的疲劳剩余寿命。在此基础上,将球轴承疲劳失效过程分为裂纹扩展和剥落点尺寸增大两部分,基于临界曲面的概念提出了改进的Paris球轴承疲劳剩余寿命预测模型,通过6205深沟球轴承试验数据验证了该模型的有效性。
4.针对球轴承疲劳剩余寿命的在线预测问题,将振动信号数据分析与微观形貌检测相结合,提出球轴承疲劳剩余寿命在线预测模型。针对球轴承未出现异常信号时疲劳剩余寿命的预测问题,将历史疲劳寿命数据的统计特征量作为先验知识,以权重函数的方式引入预测模型中,实现对个体球轴承疲劳寿命和疲劳剩余寿命的在线预测,并通过试验验证了上述两种模型的有效性。
总之,本文基于非线性动力学深入分析球轴承缺陷的生长机理,通过改进的EMD方法提取球轴承性能退化特征量,并给出了疲劳寿命与缺陷生长过程之间的关系。在此基础上,充分利用球轴承宏观统计寿命特征,结合Paris理论可预测个体球轴承疲劳剩余寿命的特点,提出球轴承疲劳剩余寿命预测模型,实现个体球轴承疲劳剩余寿命的在线预测,对有效实施设备健康管理、故障诊断与视情维修具有重要的意义。
As an important category of rolling element bearing, ball bearing is widely used in mechineries. But as a vulnerable part, ball bearing is one of the primary sources of mechinery failure. The failure without precognition not only baffles the establishment of maintenance policy, but also may bring about catastrophic accidents. So the residual fatigue life prediction of ball bearing is helpful in cognizing the health of mechanics and optimizing the maintenance policy of mechanical system. Most traditional methods of residual fatigue life prediction of ball bearings are probability-based prognosis techniques which only can estimate the overall life of ball bearings. However, methods of data-driven prognosis can predict the life of a single ball bearing, but these methods are mainly dependent on state signals not faults themselves. So the accuracy and reliability of existing models are not competent when these models are used to predict the residual fatigue life of ball bearing.
In accordance with these problems, supported by the National Natural Science Foundation of China and the Ministerial-Level Pre-Research Fund, based on nonlinear dynamics of ball bearings as the basis of failure analysis, improved EMD method as the mean of fault feature extraction, the fatigue life of ball bearing is analyzed. Together with microscopy failure modes of faults, combined with the contributions of fatigue life prediction theory based on Paris, this paper is devoted to research the residual fatigue life prediction of single ball bearing in the origin of failure mechanism. The main contributions of this dissertation are summarized as follows:
1. Aiming at complex relationships in nonlinear dynamics of ball bearing with defects, nonlinear dynamic equations of ball bearing are established on the basis of balls as the objects and the adjoint equation which is used to describe the lean of inner ring to the outer ring is inducted. Together they can describe the dynamic characteristics of the single ball bearing perfectly. Then subsection functions and the defect impulse function are inducted and nonlinear dynamic equations of ball bearing with a single surface defect are proposed on the basis of proposed nonlinear dynamic equations of ball bearing and the impact energy equations are enduced. Then nonlinear dynamic characteristics of ball bearing with a single surface defect can be described by analytical methods and it provides a theoretical basis for investigating fatigue failure mechanism in depth.
2. In order to improve the accurance of performance degenerate values of ball bearings extracted by Empirical Mode Decomposition (EMD), aiming at problems of boundary effect and modal confusion of EMD, mirror method and adding a small broadband white noise with zero mean into Intrinsic Mode Functions (IMFs) with modal confusion and then decomposed by EMD again are used to solve these problems. On this basis, combining with the improved EMD standardization process, an improved EMD method to improve the accuracy of performance degenerate values of ball bearings is proposed. Finally, the improved EMD method is applied to extract the performance degenerate values of ball bearings, together with grey model, a residual fatigue life prediction model is proposed and is verified by historial data of 6205 deep groove ball bearing. Based on this, the application of performance degenerate values in residual fatigue life prediction is analyzed and it shows that the performance degenerate values extracted by improved EMD can describe the health of ball bearing.
3. According to micro-morphology of fatigue spalling, based on critical plane, the concept of critical surface is presented, then the three-dimensional crack propagation of ball bearings is transformed into two-dimensional and this enables the traditional method can be applied in them. Based on this, the fatigue life of ball bearings is divided into two parts: fatigue crack growth and fatigue spalling propagation. Then a residual fatigue life prediction model of ball bearing is proposed based on improved Paris law and its efficiency is verified by historical lives of 6205 deep groove ball bearings.
4. Aiming at residual fatigue life prediction of ball bearings on line, by combining data analysis of vibration signals with investigation of micro-morphology observation and analysis of fatigue spalling, the on-line prediction of residual fatigue life of ball bearing is proposed. Aiming at the life prediction in the phase before the appearance of detectable exceptional signals, history life data is treated as a prior knowledge and introduced into the proposed prediction model as a weighting function and then a prediction model which can predict the fatigue life and residual fatigue life of ball bearing on line is proposed. Then the validity of the model is verified by experimental data.
In summary, this paper launched the study on defect growth mechanism based on nonlinear dynamics theory of fault ball bearings and fault feature extraction by the improved EMD method. Based on this, the relationship between fatigue life and defect growth process is investigated. On the basis of this, utilizing the macroscopical statistics of fatigue life evaluated by traditional fatigue life prediction, combining with the advantage of Paris law which can predict the residual fatigue life of the single ball bearing, a residual fatigue life prediction model is proposed. The model can be used to predict the residual fatigue life and fatigue life of the single ball bearing on line. This fills the blank of on-line prediction methods of the single ball bearing and it is helpful for health management, failure diagnosis and condition-based maintainance.
引文
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