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Vibration load identification based on the neural network model

机译:基于神经网络模型的振动载荷识别

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The paper utilizes the neural network method to identify the loads of the WZ12–1 offshore platform. Firstly, the finite element model of the WZ12–1 platform is build using the software of ANSYS. By applying loads to the identification points of the finite element model, we can obtain the data for training a neural network model. Then, a three-layer BP network is established and trained until converges using the data obtained previously. Finally, we input the actual response data into the trained network and obtain the corresponding loads on the WZ12–1 platform. The results show that the neural network method could gain a great advantage over the traditional techniques in the load identification of offshore platforms which are large and complex.
机译:本文利用神经网络方法来识别WZ12-1海上平台的载荷。首先,使用ANSYS软件建立WZ12-1平台的有限元模型。通过将载荷施加到有限元模型的识别点上,我们可以获得用于训练神经网络模型的数据。然后,建立并训练三层BP网络,直到使用先前获得的数据收敛为止。最后,我们将实际的响应数据输入到经过训练的网络中,并在WZ12-1平台上获得相应的负载。结果表明,在大型,复杂的海上平台载荷识别中,神经网络方法具有比传统技术更大的优势。

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