Abstract
Modal analysis of journal bearings is critical to their condition monitoring, dynamic analysis and damage detection by extracting the frequency, dam** ratio and mode shape based on vibration response. Operational modal analysis (OMA) which just need the output-only response has been applied in civil engineering structures successfully. In this paper, the basic procedures of the popular operational modal analysis method, that data driven stochastic subspace identification (Data-SSI) and stabilization diagram is first introduced in details. Then, a five degree of freedom model is presented to verify the accuracy and robustness of the method in identifying frequency and dam** ratio. And then, experiments under different operating conditions were conducted to acquire the vibration responses of journal bearings. The experimental modal analysis (EMA) method and Data-SSI were applied to identify free modal parameters and operational modal parameters separately. Finally, it is indicated that Data-SSI can identify modal parameters of journal bearings in operation effectively by comparing the modal parameters identified from Data-SSI with the peak values of spectrum.
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Wang, X., Feng, G., Liang, X., Zhen, D., Zhang, H., Shi, Z. (2023). Operational Modal Analysis of Journal Bearings Based on Stochastic Subspace Identification. In: Zhang, H., Ji, Y., Liu, T., Sun, X., Ball, A.D. (eds) Proceedings of TEPEN 2022. TEPEN 2022. Mechanisms and Machine Science, vol 129. Springer, Cham. https://doi.org/10.1007/978-3-031-26193-0_40
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DOI: https://doi.org/10.1007/978-3-031-26193-0_40
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