A Fault Identification Method for Autonomous Underwater Robot Based on Wavelet Approximate Entropy

Abstract

The invention relates to the technical field of autonomous underwater robot fault identification and fault-tolerant control, in particular to an autonomous underwater robot fault identification method based on wavelet approximate entropy. The invention includes: adopting multi-layer wavelet decomposition method to decompose the sensor and controller data of autonomous underwater robot; adopting approximate entropy extraction method to extract fault features from wavelet detail coefficient and wavelet approximation coefficient obtained in step (1.2); adopting correlation coefficient Methods Fault identification was carried out on the fault signal of the autonomous underwater robot to be tested. The method of the invention not only effectively solves the problem that the AUV sensor and controller signals are affected by external interference, and the fault identification accuracy is low, but also uses the multi-band characteristics of multi-layer wavelet decomposition to obtain a redundant description about the fault of the AUV thruster, and through Simultaneously extract fault features for multi-band fault information and build a fault feature matrix to improve the accuracy of AUV fault identification and provide accurate fault information for fault-tolerant controllers.

Description

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

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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

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