船舶推进轴系纵向振动位移高精度预测方法研究
Study on High-Precision Prediction Method of Longitudinal Vibration Displacements in Ship Propulsion Shaft System
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摘要: 【目的】鉴于轮机舱测点布置有限，推进轴系纵向振动只能在有限位置进行测量，导致难以全面评估整个轴系的纵振状态。本文旨在提出一种新方法，仅凭有限个测点数据即可准确预测整个推进轴系的纵向振动位移。【方法】创新性地将Kalman滤波技术与推进轴系纵向振动模型相融合，构建了一种全新的轴系纵向振动位移预测方法。该方法是一种融合确定性分析与随机性考量的时域预测方法，能够全面考虑动力学模型误差及数据测量误差的影响，通过实施最小方差无偏估计策略，有效提升位移预测精度，尤其针对螺旋桨激励力未知且测量信号面临显著噪声干扰的复杂工况，该方法仅需依据两个测量点的数据输入，即可实现对推进轴系任意位置纵向振动位移的准确预测。【结果】在信噪比低至10dB的恶劣环境下仍有较高精度，螺旋桨处预测位移与理论位移间的均方根误差仅为3.35μm，推力轴承处的均方根误差仅为1.74μm，充分证明了该方法在低信噪比环境下的高精度预测能力。【结论】本文提出的方法可为舰船推进轴系纵向振动状态的实时、在线评估提供新的解决方案，具有重要的应用价值。Abstract: [Objectives] Due to the limited placement of measurement points in the machinery space, the longitudinal vibration of the propulsion shaft system can only be measured at limited locations, making it difficult to comprehensively assess the longitudinal vibration status of the entire shaft system. This study aims to propose a new method that can accurately predict the longitudinal vibration displacement of the entire propulsion shaft system based on a limited number of measurement points. [Methods] Innovatively integrating Kalman filtering technology with the longitudinal vibration model of the propulsion shafting, a new prediction method for the longitudinal vibration displacement of the shafting is developed. This method is a time-domain prediction approach that combines deterministic analysis with stochastic considerations, fully accounting for the impacts of dynamic model errors and data measurement errors. By implementing a minimum variance unbiased estimation strategy, it effectively enhances the accuracy of displacement prediction. Especially in complex scenarios where the propeller excitation force is unknown and the measurement signals are significantly contaminated by noise, this method can accurately predict the longitudinal vibration displacement at any position of the propulsion shafting based on data input from only two measurement points. [Results] Even in harsh environments with a signal-to-noise ratio as low as 10 dB, the method maintains high accuracy. The root mean square error (RMSE) between the predicted displacement at the propeller and the theoretical displacement is only 3.35μm, and the RMSE at the thrust bearing is only 1.74 μm. These results fully demonstrate the high-precision prediction capability of this method in low signal-to-noise ratio environments. [Conclusions] The method proposed in this paper provides a new solution for real-time, online assessment of the longitudinal vibration state of ship propulsion shafting, possessing significant application value.
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