Correlation analysis and fault detection of current and speed signals for underwater thruster entanglement

Abstract

The fault detection with a single sensor cannot comprehensively use the multi-sensor correlation information of underwater thruster. To solve the issue that in the case of entanglement, a kind of fault diagnosis method of underwater thruster based on the combination of current and rotational speed signal correlation analysis and support vector machine is proposed. Firstly, the collected current and speed signals of underwater thrusters under different states are normalized, the variable sampling data points is adopted to refine the time of fault occurrence; Secondly, the cross correlation and autocorrelation coefficients of normalized current and speed signals are calculated based the variable sampling data points number and the correlation matrix is formed at different sampling time based on the cross correlation and autocorrelation coefficients. Finally, the support vector machine was applied to diagnose whether or not the fault produces and the time of fault occurrence with the correlation coefficients sequence. To verify the effectiveness of the proposed method, the fault simulation platform and data acquisition software are designed, the fault data in the case of thruster with entanglement are collected in time to test the proposed method. The results show that compared with the fault diagnosis method using only one speed or current signal, the proposed analytical method based on the correlation coefficients can fully extract the correlation information of underwater thruster fault, and the time extraction of fault occurrence is more sufficient, effectively improving the accuracy of underwater thruster fault diagnosis.