A Fault Diagnosis Method for INS/DVL/USBL Integrated Navigation System Based on Support Vector Regression

Jing Liu, Yanhui Wei, Shenggong Hao
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引用次数: 4

Abstract

For the problem of fault subsystem identification in INS/DVL/USBL integrated navigation system, a fault diagnosis method based on SVR for INS/DVL/USBL integrated navigation system is proposed to improve the reliability of underwater robot integrated navigation system. The method firstly realizes the fault diagnosis of the integrated navigation system by the residual test method, but the traditional residual test method can only detect the fault and cannot accurately identify the fault subsystem. Therefore, a regression prediction model based on support vector machine is constructed to predict the state of the inertial navigation system. The fault diagnosis of the inertial navigation is assisted according to the difference between the output of the system model and the output of the prediction model, so as to identify the fault source of the system. Simulation experiments show that the method can diagnose the fault subsystem quickly and accurately. Through fault isolation and system reconstruction, the accuracy of the navigation system can be guaranteed, and the reliability and anti-interference of the integrated navigation system can be improved.
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基于支持向量回归的INS/DVL/USBL组合导航系统故障诊断方法
针对INS/DVL/USBL组合导航系统故障分系统识别问题,提出了一种基于SVR的INS/DVL/USBL组合导航系统故障诊断方法,以提高水下机器人组合导航系统的可靠性。该方法首先通过残差测试方法实现了综合导航系统的故障诊断,但传统的残差测试方法只能检测故障,不能准确识别故障子系统。为此,构建了基于支持向量机的回归预测模型来预测惯性导航系统的状态。根据系统模型输出与预测模型输出的差异,辅助惯性导航的故障诊断,从而识别系统的故障源。仿真实验表明,该方法能够快速准确地诊断出故障子系统。通过故障隔离和系统重构,可以保证导航系统的精度,提高组合导航系统的可靠性和抗干扰性。
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