【摘要】 鉴于目前主流齿轮裂纹故障检测方法所存在的局限性(即仅利用系统响应作为研究对象,很少考虑输入对于故障特征提取的作用),并考虑到其作为一种典型非线性系统所蕴含的动态特性,将Volterra级数理论应用于不同状态齿轮啮合传动系统,以充分发挥Volterra级数能够综合利用系统输入、输出数据进行系统非线性特性描述的优势;同时考虑到QPSO算法较高的全局搜索能力,采用该算法对齿轮啮合传动系统Volterra模型进行了时域核辨识。仿真实验结果表明,高阶时域核对于齿轮裂纹故障所引起的系统非线性特性变化非常敏感,可以有效地表征并区分出不同状态下齿轮啮合传动系统的非线性动态特性,达到了预期目的。更多还原

【Abstract】 In view of the limitation of current mainstream methods of gear crack fault detection(that is only using the system response as research object, and seldom considering the input effect on fault feature extraction), and taking into account its dynamic characteristics as a kind of typical nonlinear system, by applying Volterra series theory into different states of gear meshing transmission system, for fully taking the advantage of Volterra series, which can use both the input and output data of system to describe the nonlinear characteristics of system. Meanwhile, using the high global search capability of QPSO algorithm, QPSO algorithm is used to identify the time domain kernel of gear meshing transmission system’s Volterra model(referred to as GIRF). The simulation results show that the high-order GIRFs are very sensitive to the nonlinear characteristics of the system caused by the gear crack failure, and can effectively characterize and distinguish the nonlinear dynamic characteristics of the gear meshing transmission system under different conditions. The simulation results achieve the expected purpose.更多还原