Autonomous underwater robot fault identification method based on wavelet approximate entropy

Abstract

The invention relates to the technical field of fault identification and fault-tolerant control of an autonomous underwater robot, in particular to an autonomous underwater robot fault identification method based on a wavelet approximate entropy. The autonomous underwater robot fault identification method includes the steps that sensor and controller data of the autonomous underwater robot are decomposed through a multi-layer wavelet decomposition method; fault characteristics of a wavelet detail coefficient and a wavelet approximation coefficient obtained in the step (1.2) are extracted through an approximate entropy extraction method; fault identification is carried out on to-be-detected fault signals of the autonomous underwater robot through a correlation coefficient method. The autonomous underwater robot fault identification method based on the wavelet approximate entropy effectively resolves the problems that an AUV sensor and a controller are affected by external disturbance and are low in fault identification accuracy, obtains the redundant description related to the faults of an AUV propeller through the multi-band frequency characteristic of multi-layer wavelet decomposition, extracts fault characteristics of the multi-band frequency fault information to form a fault characteristic matrix, improves the fault identification accuracy of the AUV, and provides accurate fault information for the fault-tolerant controller.

Description

Technical field [0001] The invention relates to the technical field of fault identification and fault-tolerant control of an autonomous underwater robot, in particular to a fault identification method of an autonomous underwater robot based on wavelet approximate entropy. Background technique [0002] As land resources are declining, the pace of human development of the ocean is getting faster and faster. Autonomous Underwater Vehicle (AUV: Autonomous Underwater Vehicle) is currently the only vehicle capable of detecting and developing in the deep sea without human beings, and has been highly valued by researchers at home and abroad. The thruster is the most important executive part of the AUV and has the heaviest load. Once it fails, it will directly affect the safety of the AUV. Most of the fault-tolerant control methods based on the secondary thrust distribution require accurate thruster failure. The identification of the failure degree of AUV thrusters under external interfe...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to overcome the deficiencies of the prior art, provide an autonomous underwater robot fault identification method based on wavelet decomposition and approximate entropy, and solve the problem that the autonomous underwater robot is affected by external interference and measurement noise and only extracts the time The problem of low accuracy in the identification of non-linear fault features in domain signals

Images