基于有限测点信息的管路振动载荷识别方法研究

Identification method of pipeline vibration loads with limited measurement information

摘要

提出和验证了基于有限测点信息对管路系统进行振动载荷参数识别的方法。开展了典型发动机管路振动正问题有限元建模，并对所建有限元模型的有效性进行了实验验证；基于奇异值分解算法、遗传算法和禁忌搜索算法，提出和验证了对管路系统未知振动载荷信息进行重构识别的方法，实现了基于仿真信号和振动测量信号的载荷重构。结果发现：基于最小二乘法和奇异值分解算法的载荷重构计算速度快但易受信号噪声的影响，而遗传算法和禁忌搜索算法具有更好的鲁棒性，针对仿真和实测振动信号均可实现振动载荷的有效重构。

Abstract

In this paper, methods for identification of vibration load parameters of pipeline system based on information of limited measurement points are proposed and validated. We make finite element simulation modelling for the forward vibration analysis of typical rocket engine pipelines; experimental verification of the forward finite element numerical model, establishment of methods for identification of the unknown load parameters of the pipeline system based on the singular value decomposition, genetic algorithm and Tabu search optimization algorithm, and validation using simulated and measured vibration signals at limited points. The numerical results show that the load reconstruction based on the singular value decomposition method is fast, but is easily affected by signal noise, while the genetic algorithm and the Tabu search algorithm have better robustness and can reconstruct the load parameters efficiently for both the simulated and measured vibration signals.

关键词

奇异值分解法 / 遗传算法 / 禁忌搜索算法 / 载荷识别 / 管路振动

Key words

singular value decomposition / genetic algorithm / Tabu search / load identification / pipeline vibration

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