变工况机械动态信号瞬时耦合的理解、识别与故障预示

Suffering from the nonlinearity of mechanical system, dynamic signals of machinery are non-stationary and nonlinear in nature. In varying operating condition, feature frequencies reflecting equipment fault are varying with the work condition, and system transfer function also changes instantaneously. Affected by these factors, the signal nonlinear coupling relationship and coupling degree also change instantaneously, which brings new challenges for fault feature extraction. Therefore, study on dynamic signal feature extraction method and fault diagnosis under varying operating condition is not only of the theory and engineering prospect, but also the frontier science problem in mechanical fault diagnosis field in recent years. In this project, dynamic signal nonlinear instantaneous coupling mechanism in varying operating condition is investigated firstly, on this base, an adaptive instantaneous wavelet bispectrum is proposed for nonlinear instantaneous coupling feature detection of the dynamic signal. After that, a varying operating condition fault diagnosis method is established by using the nonlinear instantaneous coupling feature of the dynamic signal. Those methods developed in this project could not only form a solid foundation for the state evaluation and fault diagnosis of machinery in variable operating conditions, but also provide a guideline for the healthy monitor of the key components such as gearbox, rolling element bearing, ball screw and so on.

实际机械系统的非线性特征使得表征其运行状态的动态信号具有本质上的非平稳与非线性特性。在变工况条件下，不仅反映设备故障的特征频率会随着工况变化，同时系统的传递函数也是时变的，并使得信号内在非线性耦合关系以及耦合程度瞬时变化，为故障特征提取带来新的挑战。开展变工况动态信号的特征提取和故障预示方法研究不仅具有切实的理论意义和工程应用前景，也是机械故障诊断领域近年来研究的前沿科学问题。在这一背景下，课题从变工况机械动态信号非线性瞬时耦合机制研究入手，结合变工况动态信号的耦合特点，研究适用于非平稳信号非线性瞬时耦合特征识别的自适应瞬时小波双谱方法，并以此为基础，建立基于动态信号非线性瞬时耦合特征的变工况故障预示方法。相关研究工作可为变工况机械设备的状态评估与故障预示提供理论基础，并可望为变工况条件下的齿轮箱、滚动轴承、滚珠丝杠等关键回转部件的故障识别等工程应用提供技术手段。

实际机械系统的非线性特征，使得表征其运行状态的动态信号具有本质上的非平稳与非线性特性。在变工况条件下，不仅反映设备故障的特征频率会随着工况变化，同时系统的传递函数也是时变的，并使得信号内在非线性耦合关系以及耦合程度瞬时变化，为故障特征提取带来新的挑战。在这一背景下，本项目围绕动态信号非线性耦合机制、瞬时非线性耦合自适应提取方法、基于二次非线性耦合特征的状态评估技术等科学问题开展研究工作。在本项目的资助下，相关研究成果在本领域SCI期刊发表论文4篇；申请国家发明专利2项。本项目的主要研究内容和创新成果总结如下：.1. 通过理论建模及现场跟踪测试，分析动态信号非线性耦合在频域上的表现形式，为基于耦合检测的设备健康状态评估提供理论依据。.2. 提出了变工况机械动态信号非线性耦合的自适应提取方法，并在时频域中揭示了设备故障与信号频率耦合关系之间的映射关系，为变工况机械设备健康状态评估及故障预示提供方法支撑。.3. 提出了基于等效扭矩二次非线性瞬时耦合特征的颤振识别方法，克服了传统的基于连续小波谱积分方法易受干扰的缺陷，实现了精密磨齿加工早期颤振的准确识别。.4. 提出了基于内置光栅尺增量信息解耦的位置脉动测试方法，并将其运用于精密机床主轴振动的在线动平衡，克服了现有商业动平衡系统在工业现场在线平衡中的局限性。.本项目取得的研究成果可为变工况机械设备的健康状态评估与故障诊断提供理论基础，并为精密加工设备的性能退化评估提供技术手段。