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VIBRATION MEASUREMENT AND LOAD IDENTIFICATION OF OFFSHORE PLATFORMS

机译:海上平台的振动测量和载荷识别

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The vibration measurement and load identification of offshore platforms were performed in this paper, where the neural network is introduced in order to overcome the disadvantages of the commonly used method. The first step is to establish a finite element model of the platform using ANSYS software. The training data of neural network is obtained by applying simulation to get response at the identification point of the model. The neural network model of the platform is then set up. The network is trained until the convergence state by using the above data. Finally, the vibration load identification for W12-1 oil production platform is performed using the method, where the measured response data are inputted to the trained network and the identification loads of the platform are obtained. The results indicate that there are more advantages of the method as compared with commonly used load identification method when used for such large and complex structures as offshore platforms and the identification accuracy of the method is satisfactory.
机译:本文进行了海上平台的振动测量和载荷识别,引入了神经网络,以克服常用方法的缺点。第一步是使用ANSYS软件建立平台的有限元模型。通过应用仿真获得神经网络的训练数据,以在模型的识别点获得响应。然后建立平台的神经网络模型。通过使用以上数据,可以训练网络直到收敛状态。最后,利用该方法对W12-1采油平台进行振动载荷识别,将测得的响应数据输入到训练网络中,得到平台的识别载荷。结果表明,该方法用于大型复杂结构如海上平台时,与常用的载荷识别方法相比,具有更多的优势,识别精度令人满意。

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