Multiple load recognition and fatigue assessment on longitudinal stop of railway freight car

Safety evaluation of key support components remains a challenge for freight trains because of the difficulties in direct and precise monitoring. In this work, the longitudinal stop on well-hole freight train, which prevents the cargo from sliding in anterior-posterior direction, is investigated. Load identification approach is proposed via strain perception at multiple locations, which are selected from the optimal positions sensitive to longitudinal and lateral loading in Finite Element Analysis (FEA). Validation is performed in random loading simulations. The identified loads deviate from the random sets within 4.07%. Longitudinal and lateral forces are recognized in an attempt to calculate the signed von Mises (SVM) stress of the longitudinal stop structure for fatigue evaluation. In application, the reconstructed structural stress climbs up to 107.1 MPa for the right weld base. Employing the rain-flow counting and Miner's damage rule, the recommendation for load spectra grade in convergence is 64 groups. The equivalent fatigue damage is 0.854 and it drops to 30% in the statistical annual maximum mileage equivalency. Research outcome reveals that the proposed method enables the real-time monitoring of service loads and structural stress in railway freight transport, which provides scientific evidence for its maintenance planning and structural optimization.