Nonlinear dynamic analysis of misalignment-impact coupling fault in a dual-span rotor system

This study investigates the nonlinear dynamic performance, including vibration characteristics, of a dual-span main shaft system. The analysis employs a self-developed passion fruit pulping mechanism as a case study, with particular emphasis on the quick-insert shaft sleeve coupling. The primary objective is to enhance the operational stability of the passion fruit pulping mechanism, particularly under nonlinear factors such as rotor misalignment forces and rolling bearing impact forces. A nonlinear motion model for the dual-span pulping mechanism rotor system was established using the lumped mass method. Motion differential equations for mass points were derived by integrating Newton's second law with Lagrange's equation. Following this, harmonic response and multi-body dynamics analyses were conducted on the dual-span rotor system. Finite element analysis and Adams dynamics simulation software were utilized to assess the resonance characteristics and operational stability of the system. The U-Net semantic segmentation network algorithm was employed in experimentation to achieve visual measurement of vibrations in the rotating spindle. Analysis of time displacement curves, frequency displacement curves, and shaft center trajectory plots indicates that an increase in rotational speed of the pulp extraction mechanism results in fluctuating rotor amplitudes. An optimal operating condition was identified at 250.2 r/min. Furthermore, increasing misalignment at a constant rotational speed results in an enhanced rotor vibration response. Rotor vibrations in both horizontal ( x, y ) directions remain largely consistent within reasonable ranges of speed and misalignment. This research provides a theoretical foundation for developing dual-span rotor systems featuring quick-insert shaft sleeve coupling within agricultural processing contexts while considering nonlinear effects. These findings hold significant engineering value for understanding system stability.