Approach to Receptance Coupling Substructure Analysis based on Full Receptance Estimation of Sub-assembly Using the Modal Fitting Method

Understanding and optimizing the dynamic characteristics of machine tools are essential for improving the efficiency and precision of manufacturing processes. An effective method for dynamic characteristic prediction and analysis of various tools is receptance coupling substructure analysis. Precision receptance coupling substructure analysis requires a frequency response function for the rotational degrees of freedom. Although computing the full receptance matrix, which includes rotational degrees of freedom, is possible through mathematical methods or finite element method, it is time-intensive and impractical for industrial applications due to the need for additional sensor attachments or other attachments on machinery. This study proposes a new approach for the receptance coupling substructure analysis of cutting tools and holders, aiming to efficiently predict and couple the full receptance matrix of cutting tools under free-free condition. The proposed methodology divides the cutting tool into several substructures and employs receptance coupling based on Euler–Bernoulli beam theory, thereby estimating the full receptance matrix of the subassembly. This approach also enables the prediction of dynamic characteristics of the system through inverse receptance coupling with a holder. We validated the accuracy of the methodology using the finite element method and experimental methods. The full receptance matrix of the machine tool and the estimated cutting tools were coupled and experimentally verified. In addition, the applicability of the proposed methodology is ensured by performing receptance coupling for various tool overhang lengths. This study is expected to contribute significantly to the quality improvement, design, and performance enhancement of machining equipment in the manufacturing industry. Further research is required to validate the robustness of this methodology across tools with diverse geometries and shapes.