• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Mathematical Problems in Engineering >Research on Fault Evolution Feature Extraction and Identification of Sun Gear Cracks in Planetary Gearbox Based on Volterra High-Order Kernel Generalized Frequency Response Graphic Analysis
【24h】

Research on Fault Evolution Feature Extraction and Identification of Sun Gear Cracks in Planetary Gearbox Based on Volterra High-Order Kernel Generalized Frequency Response Graphic Analysis

机译：基于Volterra高阶核广义频响图形分析的行星齿轮箱太阳齿轮裂纹演化特征提取与识别研究。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, relying on the Volterra series nonlinear system model and the high-order kernel Hilbert's reconstructed kernel fast solved algorithm, a fault feature frequency domain identification method based on Volterra high-order kernel generalized frequency response graph analysis is proposed. Firstly, the method uses the system input and output vibration signals to determine the Volterra model. Then, the Volterra high-order kernel function is solved quickly by reproducing kernel Hilbert space method, and the generalized frequency response function is used to identify the model. Finally, multidimensional high-order spectral pattern analysis is used to separate and extract the fault and degree characteristic information implied by frequency and phase coupling in the third-order kernel function. Following the theoretical approach, in the experimental part, this paper uses the planetary gearbox fault loading test rig to complete the data collection and establishes the Volterra experimental model through the measured data. The generalized frequency responses of each order kernel function are compared and analyzed and the capability of distinguishing and the adaptability of different order kernel functions for the degree of crack failure are discussed. The effects of changing the memory length of the Volterra model and the order of the kernel function on the recognition result are verified. The final experimental results show that the use of reproducing kernel Hilbert space can effectively avoid the dimension disaster problem that occurs in the high-order kernel solution process. Moreover, the third-order kernel can describe more intuitively the nonlinear system model under multifactor coupling than the second-order kernel. Finally, Volterra series model the third-order kernel's generalized frequency response can effectively distinguish between nondefective and faulty gears, and its resolution is enough to distinguish the degree of failure of gear cracks.
机译：本文基于Volterra级数非线性系统模型和高阶核Hilbert重构核快速求解算法，提出了一种基于Volterra高阶核广义频率响应图分析的故障特征频域识别方法。首先，该方法使用系统的输入和输出振动信号来确定Volterra模型。然后，通过重现内核Hilbert空间方法快速求解Volterra高阶内核函数，并使用广义频率响应函数识别模型。最后，利用多维高阶谱模式分析来分离和提取三阶核函数中频率和相位耦合所隐含的故障和程度特征信息。按照理论方法，在实验部分，本文使用行星齿轮箱故障载荷试验台完成数据收集，并通过测量数据建立Volterra实验模型。对各阶核函数的广义频率响应进行了比较和分析，讨论了不同阶核函数对裂纹破坏程度的区分能力和适应性。验证了改变Volterra模型的存储长度和核函数的阶数对识别结果的影响。最终的实验结果表明，使用可再生内核Hilbert空间可以有效避免高阶内核求解过程中发生的尺寸灾难问题。而且，与二阶内核相比，三阶内核可以更直观地描述多因素耦合下的非线性系统模型。最后，Volterra级数模型对三阶核的广义频率响应进行了建模，可以有效地区分齿轮的有缺陷和故障，并且其分辨率足以区分齿轮裂纹的失效程度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号