Fault identification method for autonomous underwater robot based on wavelet fractal
A technology for underwater robot and fault identification, which is applied in the direction of instruments, electrical testing/monitoring, control/regulation systems, etc., can solve the problems of autonomous underwater robot interference measurement noise, low accuracy of nonlinear fault feature identification, and influence , to achieve good denoising effect, improve computing speed, and simple algorithm
Active Publication Date: 2017-06-20
HARBIN ENG UNIV
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[0006] The purpose of the present invention is to provide a combination of wavelet decomposition and fractal features, which can effectively solve the problem that autonomous underwater robots are affected by external interference and measurement noise, and the accuracy of nonlinear fault feature identification is low only by extracting time-domain signals. Fault identification method for autonomous underwater robot based on wavelet fractal
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[0033] combine figure 1 , based on the multi-layer wavelet decomposition method and the fractal fault feature extraction method, the implementation steps are as follows:
[0034] (1) First, the sliding window processing is performed on the data collected by the autonomous underwater robot. When the sensor and controller signals with a data length of L=200 are collected, the detection algorithm is started, and when new data is collected again, discard The first data of the original array and the newly collected data are placed at the end of the original array, and the data length is always kept at L=200;
[0035] (2) Perform multi-layer wavelet decomposition on the data in the array in the sliding window. Decomposition process: select an appropriate wavelet basis function "db1", determine the number of decomposition layers as 3 layers, perform multi-layer wavelet decomposition on the original data of the sensor and the control quantity highly related to the sensor signal, and ...
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The invention provides an autonomous type underwater robot fault identification method based on a wavelet fractal. The autonomous type underwater robot fault identification method comprises the following steps: performing multilayered wavelet decomposition on an autonomous type underwater robot state signal so as to inhibit influence of external random interference on accuracy of identification, fault description on multiple frequency sections of an autonomous type underwater robot booster, and improve fault identification precision; extracting fractal characteristics from a wavelet approximate coefficient and a wavelet detail coefficient obtained through decomposition of multilayered wavelets, and forming a fractal feature matrix; calculating related coefficient of fractal characteristics in a sample feature matrix established through a pond test at early period, and obtaining fault identification result of the booster. The autonomous type underwater robot fault identification method is applicable to solve the problem that the autonomous type underwater robot fault is influenced by external random interference and the accuracy of the booster fault degree is low; moreover, the method improves the fault identification precision, and can be applied to the fault identification, fault-tolerant control and other fields of the autonomous type underwater robot booster.
Description
technical field [0001] The invention relates to a method for fault identification and fault-tolerant control of an autonomous underwater robot, in particular to a method for fault identification of the fault degree of a thruster of an autonomous underwater robot based on wavelet decomposition and fractal. 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...
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IPC IPC(8): G05B23/02
CPCG05B23/0221
Inventor 张铭钧刘维新刘星殷宝吉王玉甲赵文德姚峰
Owner HARBIN ENG UNIV