Dynamic model updating based on finite element method (FEM) has been widely investigated for structural damage identification, especially for static structures. Despite the substantial advances in this method, the key issue still needs to be addressed to boost its efficiency in practical applications. This paper introduces the updating idea into crack identification for rotating rotors, which has been rarely addressed in the literature. To address the problem, a novel Kriging surrogate model-based FEM updating method is proposed for the breathing crack identification of rotors by using the super-harmonic nonlinear characteristics. In this method, the breathing crack induced nonlinear characteristics from two locations of the rotors are harnessed instead of the traditional linear damage features for more sensitive and accurate breathing crack identification. Moreover, a FEM of a two-disc rotor-bearing system with a response-dependent breathing crack is established, which is partly validated by experiments. In addition, the associated breathing crack induced nonlinear characteristics are investigated and used to construct the objective function of Kriging surrogate model. Finally, the feasibility and the effectiveness of the proposed method are verified by numerical experiments with Gaussian white noise contamination. Results demonstrate that the proposed method is effective, accurate, and robust for breathing crack identification in rotors and is promising for practical engineering applications.

The crack breathing model and crack identification method for rotors using nonlinearity induced by cracks are studied in this work. Firstly, the finite element method is utilized to model a rotor–bearing system with a response-dependent breathing crack to obtain the numerical data for crack identification. During the modelling, an improved breathing crack model is proposed, focused on the unreasonable assumption about crack closure line in the original crack closure line position (CCLP) model. Compared with the original model, the improved breathing model can reflect the nonlinear behavior of cracks better. Secondly, based on the established model, super-harmonic features at 1/3 and 1/2 of the critical rotating speeds under different crack locations and crack depths are extracted for crack identification. Additionally, the super-harmonic features from two measurement points are used as inputs into an artificial neural network with a Levenberg–Marquardt back-propagation algorithm, corresponding crack positions and depths as outputs. The robustness of the method is tested by examining the identification results under different levels of noise. The results show that the proposed crack identification method is efficient for simultaneous identification of crack depth and position in operating rotors.

Metal structures of ladle cranes are typical complex welded structures, where fatigue cracks are prone to initiate in some specific locations. In this paper, on-site tests and theoretical analysis were performed for a in-service ladle crane to investigate the crack damage mechanism at some local areas beneath the wheel loads. The on-site tests included crack observation of the entire bridge structure, geometry inspection of the main girder and stress test of the key locations. It was found that fatigue cracks had densely occurred in some spots with similar geometry details. The stress test results showed that obvious rail gnawing phenomenon happened during the ladle crane operating process. By finite element analysis (FEA) with a multi-layer model and DLOAD subroutine, stress time histories of the damaged spots under moving wheel loads were simulated. Combined with the tested stresses, influences of rail gnawing force on the stress cycling characteristics at the cracked areas were analyzed. Based on the in-service stress spectrum, the fatigue lives of the cracked areas were predicted, revealing that the random rail gnawing force is the dominant factor causing large amount of cracks at the damaged areas.

A novel output-only crack localization method is proposed for operating rotors based on an enhanced higher-order dynamic mode decomposition (HODMD), in which the nonlinear breathing crack-induced super-harmonic characteristic components from multiple vibration measurement points are simultaneously extracted to compose the corresponding super-harmonic transmissibility damage indexes. Firstly, the theoretical background of the HODMD is briefly reviewed. Secondly, the proposed crack localization method is dedicated which improving the HODMD for multivariate signals by casting the total least square method into standard HODMD and adaptively selecting the order parameter of Koopman approximation by optimizing the super-harmonic frequency vector. In addition, the super-harmonic characteristic components are evaluated and harnessed to derive the damage index based on super-harmonic transmissibility and fractal dimension. Finally, the proposed method is investigated and demonstrated by numerical simulations and experiments. Both numerical and experimental results show that the proposed method is powerful in realizing multi-crack localization for running rotors accurately and robustly in the case of no baseline information on intact rotors. Moreover, the interferences from commonly existing steps and misalignment can also be eliminated.

The impact of rolling mill vibration extends beyond product quality to equipment health, making vibration control crucial. This study addresses the issue of frequent abnormal vibration in hot strip finishing mills by employing a combination of theory, simulation, and experimentation to analyze the dynamic behavior of the mill and apply findings to on-site vibration suppression. Initially, a torsional-vertical-horizontal coupled dynamic model for the rolling mill has been developed, taking into account the rolling process. The accuracy of this model is established through both finite element simulations and actual experiments. Subsequently, the vibration characteristics of the rolling mill system are investigated under typical process parameters utilizing the established dynamic model. The results reveal that the vibration amplitude notably escalates with the increase of rolling reduction rate and rolling speed, and the difference in front and rear tension has little impact on the mill’s vibration. Furthermore, an increase in the temperature of the rolled piece reduces the overall vibration amplitude, and harder material results in greater overall mill vibration. Lastly, abnormal vibration in the F2 finishing mill at a hot rolling plant is effectively mitigated by reducing rolling reduction rate, which further validates the correctness of the findings.