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作 者:石筱筱 叶波 邹杨坤[2,3] 曹弘贵 SHI Xiao-xiao;YE Bo;ZOU Yang-kun;CAO Hong-gui(Faculty of Irformation Engineering and Automation;Yunnan Key Laboratory of Intellige nt Control and Applications;Facudty of Civil Aviation and Aeronautics,Kunmning University of Science and Technology)
机构地区:[1]昆明理工大学信息工程与自动化学院 [2]昆明理工大学云南省智能控制与应用重点实验室 [3]昆明理工大学民航与航空学院
出 处:《化工自动化及仪表》2025年第2期289-300,共12页Control and Instruments in Chemical Industry
摘 要:针对长距离铁精矿浆输送管道在其长期过程运行中出现损伤泄漏危害巨大的情况,开展了基于超声导波的铁精矿浆输送管道结构健康监测(SHM)有限元建模与仿真。首先,使用COMSOL Multiphysics进行空管结构健康监测建模,并通过与实验结果对比进行模型验证;然后,进一步在所建立的模型中加入矿浆流动仿真模型,对实际运行工况下铁精矿浆输送管道结构健康监测进行仿真研究,利用所建模型开展了参数化仿真,计算了矿浆流速、浓度、铁精矿粉粒径、管壁裂纹对信号的影响规律。仿真计算结果表明:矿浆流速、浓度、铁精矿粉粒径变化对导波信号有一定影响,但相较于裂纹影响较小,与轴向裂纹相比,周向裂纹对信号影响更为明显。Considering both damage and leakage of the long-distance transportation pipeline for the iron concentrate pulps in operation,the finite element modeling and simulation of the structural health monitoring(SHM)of this transportation pipeline based on ultrasonic guided wave was carried out.Firstly,having COMSOL Multiphysics used to model the blank pipe structural health monitoring,and then having the model verified through comparing simulation result with the experimental result;and then,having the ion pulp flow simulation model added to the established model to simulate structural health monitoring of the transportation pipeline under actual operating conditions.In addition,having the parametric simulation carried out using the established model,and the influence law of slurry flow velocity,concentration,iron concentrate particle size and pipe wall crack on signal was simulated and calculated.The simulation results show that,the slurry flow velocity,concentration and iron concentrate particle size changes have a certain influence on the guided wave signal,but the influence is small compared with the crack,and the circumferential crack has a more obvious influence on the signal compared with the axial crack,which can provide a strong guidance for the subsequent development of the the transportation pipeline’s structural health monitoring.
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