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Weak thruster fault prediction method for autonomous underwater vehicles based on grey model

机译:基于灰色模型的自动水下航行器弱推力器故障预测方法

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摘要

When adopting the conventional grey model (GM(1,1)) to predict weak thruster fault for autonomous underwater vehicles, the prediction error is not always satisfactory. In order to solve the problem, this article develops a new weak thruster fault prediction method based on an improved GM(1,1). In the developed GM(1,1) based fault prediction method, this article mainly makes improvement in the following aspects: construction of grey background value, solution of whiting differential equation and construction of predicted sequence. Specifically, the integral operation is used in range of the two adjacent steps to obtain the grey background value at first. Second, in the solving of whiting differential equation, the point corresponding to the least difference between the accumulated generation sequence and its predicted sequence is determined, and then this special point's value in the original sequence is considered as the initial condition of the whiting differential equation. Third, in the construction of predicted sequence, another predicted value is obtained based on the error sequence between the accumulated generating operation sequence and its predicted sequence, and then the new predicted result is used to re-adjust the accumulated generating operation sequence, so as to guarantee the re-adjustability of the fault prediction result. Finally, experiments are performed on Beaver 2 autonomous underwater vehicle to evaluate the prediction performance of the developed method.
机译:当采用常规的灰色模型(GM(1,1))来预测自动水下航行器的弱推力器故障时,预测误差并不总是令人满意的。为了解决这一问题,本文提出了一种基于改进的GM(1,1)的弱推力器故障预测方法。在已开发的基于GM(1,1)的故障预测方法中,本文主要在以下方面进行了改进:灰色背景值的构造,whiting微分方程的解和预测序列的构造。具体地,首先在两个相邻步骤的范围内使用积分运算以获得灰色背景值。其次,在求解惠特微分方程时,确定与累积的生成序列与其预测序列之间的最小差对应的点,然后将原始序列中的该特殊点的值视为惠特微分方程的初始条件。 。第三,在预测序列的构造中,基于累积的发电运行序列与其预测序列之间的误差序列,获得另一个预测值,然后使用新的预测结果重新调整累积的发电运行序列,从而以保证故障预测结果的可调整性。最后,在Beaver 2自主水下航行器上进行了实验,以评估所开发方法的预测性能。

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