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A Genetic Algorithm based Inverse Problem Approach for Pedestal Looseness Identification in Rotor-Bearing Systems

机译:基于遗传算法的转子轴承座松动识别反问题方法

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摘要

Pedestal looseness is a very dangerous and frequent fault in rotating machinery. In this paper, a genetic algorithm based inverse problem approach is proposed for the identification of pedestal looseness in the rotor-bearing system. The proposed approach regards the pedestal looseness identification as an inverse problem, and formulates this problem as a multi-parameter optimization problem by establishing a non-linear dynamics model of the rotor-bearing system with the pedestal looseness, and then utilizes a genetic algorithm to search for the solution. In addition, the non-linear dynamics model and the parameter sensitiveness of the system response are investigated. The responses of the system are obtained by using the fourth-order Runge-Kutta integration. The numerical experiments suggest that good identification of the pedestal looseness is possible and the proposed approach is feasible.
机译:基座松动是旋转机械中非常危险且经常发生的故障。本文提出了一种基于遗传算法的反问题方法,用于识别转子轴承系统中的基座松动。所提出的方法将基座松动识别视为一个反问题,并通过建立具有基座松动的转子轴承系统的非线性动力学模型,将该问题表述为多参数优化问题,然后利用遗传算法进行求解。搜索解决方案。此外,还研究了非线性动力学模型和系统响应的参数敏感性。通过使用四阶Runge-Kutta积分获得系统的响应。数值实验表明,可以很好地识别基台松动,并且该方法是可行的。

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