Bayesian online diagnosis and prediction method for fatigue stratification damage of composite material

Abstract

The invention discloses a Bayesian online diagnosis and prediction method for fatigue delamination damage of a composite material. The method comprises the following steps: defining an augmented statevector comprising a structural fatigue delamination damage position variable and an area variable for the fatigue delamination damage of a composite material laminated plate; proposing a fatigue stratification damage area evolution equation based on an empirical index model and a damage position evolution equation based on a gamma process; under a Bayesian filtering theory framework, carrying outcombined diagnosis on the position and the area of structural fatigue stratified damage by combining structural strain monitoring data based on a fiber bragg grating; and predicting the future evolution process of the stratified damage area in combination with a diagnosis result to obtain the remaining service life of the structure. Online joint diagnosis of the layering damage position and areaof the composite material and prediction of the remaining service life of the structure can be effectively achieved, and the method has important application prospects in guaranteeing large-scale application of the composite material structure and achieving situation-based maintenance of the composite material structure.

Description

technical field [0001] The invention belongs to the technical field of structural health monitoring, and specifically refers to a Bayesian online diagnosis and prediction method for fatigue delamination damage of composite materials. Background technique [0002] Advanced composite materials, especially high-strength carbon fiber composite materials, have been widely used in aerospace and other fields. At present, there are still many key problems in the high-proportion application of advanced composite materials in my country. For example, compared with metal structures, composite materials have much more complex mechanical properties and failure modes; and with the development of modern equipment, composite material structures are subjected to increasingly severe loads and environmental conditions. These problems have put forward higher requirements for the safety, reliability, and life of composite material structures; thus, they have posed major challenges to the safety ...

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Problems solved by technology

[0004] Aiming at the deficiencies of the above-mentioned prior art, the purpose of the present invention is to provide a Bayesian online diagnosis and prediction method for fatigue delamination damage of composite materials, so as to solve the problem of online monitoring and prediction of composite laminate structures in the prior art existing problems

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