Underwater-robot propeller fault degree identification method based on relative-gray-correlation-degree boundary constraints
A gray correlation degree, underwater robot technology, applied in the direction of instruments, computer parts, character and pattern recognition, etc., can solve problems such as reducing the recognition accuracy
Active Publication Date: 2018-11-06
JIANGSU UNIV OF SCI & TECH
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Since the standard mode vector is a discrete value of different gears corresponding to the fault degree, based on this method, the fault degree can only identify a certain gear in the discrete standard fault degree, and it is difficult to distinguish between two standard fault degrees. Get the specific value of the fault degree, thus reducing the identification accuracy
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[0109] In this embodiment, three sets of thrusters are provided; Figure 4 is the known mode vector corresponding to the different known fault degrees of the multiple groups of propellers, according to Figure 4 In the standard mode vector library established by the known mode vectors shown, the standard fault degree is: λ 01 = 0%, λ 02 =10%, λ 03 =20%, λ 04 =30%, λ 05 = 40%.
[0110] Figure 5 is the unknown mode vector corresponding to the unknown failure degree of the thruster, and the unknown failure degree in this embodiment is: λ U1 =10%, λ U2 =13%, λ U3 =18%, λ U4 =20%, λ U5 =25%, λ U6 =30%, λ U7 =37%, λ U8 = 40%.
[0111] Figure 6 is the gray correlation degree between known pattern vectors, standard pattern vectors and standard pattern vectors in the standard pattern vector library. according to Figure 6 It can be seen that the boundary constraints of the gray relational degree corresponding to each standard failure degree are γ 01lim =0.9543, γ 0...
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The invention discloses an underwater-robot propeller fault degree identification method based on relative-gray-correlation-degree boundary constraints. The method comprises the steps of: firstly, successively obtaining known mode vectors corresponding to different known fault degrees of multiple sets of propellers, a standard mode vector library, gray correlation degrees and relative gray correlation degrees among standard mode vectors and gray correlation degrees between the known mode vectors and the standard mode vectors; then correcting a mapping function of the relative gray correlationdegrees and fault degrees on the basis of the gray-correlation-degree boundary constraints; obtaining an unknown mode vector corresponding to an unknown fault degree of a propeller, gray correlation degrees between the unknown mode vector and the standard mode vectors and the like; and judging the propeller fault degree. When the fault mode vector corresponding to a real fault falls on a certain standard mode vector point, a standard fault degree corresponding to the standard mode vector is identified; and when the fault mode vector corresponding to the real fault falls between two standard mode vectors, a specific value between two standard fault degrees is identified.
Description
technical field [0001] The invention belongs to underwater robot technology, and relates to a fault diagnosis method for a propeller of an underwater robot, in particular to a fault degree identification method for a propeller of an underwater robot based on boundary constraints of relative gray correlation degrees. Background technique [0002] Underwater robots work in complex ocean environments, and safety is one of the important research contents in the process of research and practical application of underwater robots. The thruster is the most heavily loaded and most prone to failure component of an underwater robot. Research on the fault degree identification technology of an underwater robot's thruster has important research significance and practical value for improving the safety of an underwater robot. In the aspect of thruster fault degree identification, the commonly used fault degree identification method generally establishes a fault degree classification model...
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IPC IPC(8): G06K9/62G06K9/48G06F17/16
CPCG06F17/16G06V10/469G06F18/23
Inventor 殷宝吉林溪唐文献张建苏世杰金志坤汤文宁李东昇
Owner JIANGSU UNIV OF SCI & TECH