轧机垂直系统动力学参数辨识

doi:10.13228/j.boyuan.issn0449749x.20190130

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摘要针对轧机垂直系统动力学参数可信度不足等问题，提出一种基于实测数据的改进粒子群算法辨识轧机垂直系统动力学参数的方法。首先,将轧机垂直系统刚度和阻尼考虑成达芬振子和范德波尔振子，构建轧机垂直系统非线性动力学模型，并对粒子群算法进行改进；然后，通过数值仿真算例辨识得到系统在感染噪声和不含噪声时的动力学参数，验证了该算法的有效性；最后，以现场某轧机垂直系统为研究对象，基于现场实测数据，应用该算法进行辨识，得到了轧机垂直系统动力学参数估计，通过实测位移、速度和加速度信号分别与辨识后的位移、速度和加速度信号进行对比，证明该方法辨识轧机垂直系统动力学参数结果可靠，具有一定的工程应用价值。

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关键词 ：轧机 , 粒子群 , 非线性系统 , 辨识 , 振动

Abstract：An improved particle swarm optimization (IPSO) algorithm was proposed to identify the dynamic parameters of the vertical mill system. Firstly，the stiffness and damping of the vertical system were considered as the Duffing oscillators and Vanderpol oscillators，and the nonlinear dynamic model of the vertical system was constructed. Then the PSO algorithm was improved，and the dynamic parameters of the system were identified by numerical simulation examples with noise or not，which verified the effectiveness of the algorithm. Finally，the vertical system was taken as the research object，and the algorithm was used to identify the vertical mill system dynamics parameter based on the measured data. Comparing the measured displacement，velocity and acceleration signal respectively with the identified displacement，velocity and acceleration signal，reliability of the method to identify vertical system dynamics parameters has proved. Additionally, the method has certain value in the field of engineering applications.

Key words： rolling mill particle swarm nonlinear system identification vibration

收稿日期: 2019-04-08 出版日期: 2019-11-15

PACS:

TH113.1

引用本文:

凌启辉，张维，赵前程，闫晓强，张清东. 轧机垂直系统动力学参数辨识[J]. 钢铁, 2019, 54(11): 123-129. LING Qihui1，ZHANG Wei1，ZHAO Qiancheng1，. Dynamic parameter identification of rolling mill vertical system. Iron and Steel, 2019, 54(11): 123-129.

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http://www.chinamet.cn/Jweb_gt/CN/10.13228/j.boyuan.issn0449749x.20190130 或 http://www.chinamet.cn/Jweb_gt/CN/Y2019/V54/I11/123

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