93 / 2025-05-14 21:37:34

A Twin Model Construction Method for Unbalanced Vibration in Rotor Systems Based on Random Forest

rotor unbalance,dynamic twin model,K-means clustering,finite element analysis,random forest

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Aiming at the problems of insufficient real-time monitoring of the dynamic characteristics of rotating machinery under multiple working conditions and high data acquisition costs, A twin model construction method for unbalanced vibration in rotor systems based on random forests is proposed in this paper to achieve rapid prediction of the unbalance or vibration response. Based on the finite element dynamic model, the characteristic data are obtained by applying unbalanced excitation through harmonic response analysis. Combined with the K-means clustering method, the input characteristic data is ordered to extract the dynamic characteristics of key nodes and reduce the computational load. According to the requirements of different application scenarios, a three-level prediction twin model is constructed based on the dynamic characteristics of key nodes after order reduction: Model Ⅰ for predicting unbalance, Model Ⅱ for predicting both unbalance and excitation frequency simultaneously, and Model Ⅲ for predicting the frequency response function covering the entire frequency band. A finite element model of a rotor system is used for validation. Results show that the average prediction error of Model Ⅰ is 0.092 g·m; The error of Model Ⅱ in the excitation frequency prediction is less than 1 Hz, and the average prediction error of the unbalance is 0.266 g·m. The correlations between the predicted curves and the actual values of each measurement point in Model Ⅲ all exceeded 0.98, verifying the accuracy and engineering application value of the method.