The structural vibration and dominant vibration characteristics of the machining process of machine tools have an important influence on the machining quality and efficiency. The dominant vibration characteristics are related to two factors: the dynamic characteristics of the machine tool structure and the excitation characteristics of the system. In the dynamic process of structural vibration, the participations of various modes in a certain frequency domain are often different in the vibration process; that is to say, not all modes can be excited equally, only a certain mode or some of the modes may play a major role in the specific processing conditions and dominate. Thus, these modes are called the dominant vibration modes. Therefore, this paper proposes a method of modal response signal prediction and dominant vibration mode identification under the cutting state of machine tool and studies the dominant vibration characteristics of the machine tool structure under cutting conditions. A dynamic system modeling method based on state space and modal decoupling theory is proposed. The Kalman filter algorithm is used to predict the modal response signal of the machine tool during cutting process, and the modal participation degree is analyzed based on the predicted modal response signal. In this way, the dominant vibration mode of the machine tool structure is analyzed.

机床加工过程的结构振动和主要振动特征对加工质量和效率有重要影响。主要的振动特性与两个因素有关：机床结构的动态特性和系统的激励特性。在结构振动的动态过程中，在一定的频率范围内，各种模式的参与通常在振动过程中是不同的。也就是说，并不是所有的模式都能被同等地激发，只有特定的一个或某些模式可以在特定的加工条件下起主要作用并起主导作用。因此，这些模式称为主导振动模式。因此，提出了一种切削状态下模态响应信号预测和主振动模式识别的方法，研究了切削条件下机床结构的主振动特性。提出了一种基于状态空间和模态解耦理论的动态系统建模方法。卡尔曼滤波算法用于预测切削过程中机床的模态响应信号，并基于预测的模态响应信号分析模态参与度。通过这种方式，分析了机床结构的主要振动模式。提出了一种基于状态空间和模态解耦理论的动态系统建模方法。卡尔曼滤波算法用于预测切削过程中机床的模态响应信号，并基于预测的模态响应信号分析模态参与度。通过这种方式，分析了机床结构的主要振动模式。提出了一种基于状态空间和模态解耦理论的动态系统建模方法。卡尔曼滤波算法用于预测切削过程中机床的模态响应信号，并基于预测的模态响应信号分析模态参与度。通过这种方式，分析了机床结构的主要振动模式。