Ship Hydrodynamic Pressure Signal Detection Based on Neural Network Prediction

Xiaobing Zhang, Yizhuo Jia
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Abstract

The ship hydrodynamic pressure signal is generally hard to detect from the rough ocean wave hydrodynamic pressure background signal. An algorithm based on neural network prediction is provided to detect the ship pressure signal from the ocean wave pressure signal. The predictions of hydrodynamic pressure signal are compared with measurements of the same variables to form prediction errors that are used to test for the presence of the ship pressure signal. If the prediction errors are relatively high, it will mean the appearance of a ship hydrodynamic pressure signal. Through the simulation results on the simulated and the measurement data, the algorithm based on feed forward neural network prediction proved its validity.
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基于神经网络预测的船舶动水压力信号检测
船舶动水压力信号一般难以从汹涌的海浪动水压力背景信号中检测出来。提出了一种基于神经网络预测的从海浪压力信号中检测船舶压力信号的算法。将水动压力信号的预测与相同变量的测量结果进行比较,形成预测误差,用于测试船舶压力信号的存在。如果预报误差比较大,就意味着出现了船舶动水压力信号。通过对仿真数据和实测数据的仿真结果,验证了基于前馈神经网络预测算法的有效性。
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