【摘要】 轴承动载荷是影响旋转机械安全稳定运行的重要因素。在基于频响函数求逆法的动载荷识别模型基础上，针对频响函数矩阵病态性问题，提出基于响应点优化和截断奇异值分解（Truncated Singular Value Decomposition,TSVD）法的矩阵病态消除方法。首先，选择条件数最小的测点组合进行响应点优化，再利用TSVD法识别轴承动载荷。在所搭建的双转子实验台上设计识别方案，通过改变轮盘不平衡量，验证了根据该方法识别轴承动载荷的可靠性。更多还原

【Abstract】 Bearing dynamic load is an important factor affecting the safe and stable operation of rotating machinery. In this paper, a model for recognizing dynamic load based on frequency response function inversing is established. The method based on response point optimization and truncated singular value decomposition(TSVD) is proposed to solve the ill-conditioned matrix problem of the traditional identification methods. Firstly, the measuring points with the minimum number of conditions are combined and used to the response point optimization. Then, the TSVD method is used to identify the bearing dynamic load. The reliability of this method to identify the dynamic load of bearings is verified by the experimental test on the double-rotor test bench through changing the disc imbalance.更多还原