Fatigue Crack Evaluation Method Based on Adaptive Kernel Density Estimation Assisted Particle Filter

Abstract

The invention provides a fatigue crack evaluation method based on adaptive kernel density estimation assisted particle filter, the method includes: determining the key evaluation components, constructing the state equation and observation equation of the fatigue crack random growth model, constructing the nonlinear state space model description In the evaluation process of fatigue crack growth, the simulation calculation of the crack growth state is performed on the nonlinear state space model of the fatigue crack growth of the rotorcraft structure based on the adaptive kernel density estimation assisted particle filter method. Aiming at the condition that the state model is uncertain, the present invention uses the method of kernel density estimation to correct the resampling step, so that the resampled particles maintain diversity, improves the accuracy of the filter estimation result, and uses the particle weight to propose an adaptive Based on the kernel bandwidth selection scheme, better kernel density estimation results are obtained and applied to the particle filter framework, which improves the estimation accuracy of fatigue crack growth, thereby improving the safety of the rotorcraft structure during use.

Description

technical field [0001] The invention belongs to the technical field of computer simulation, in particular to a fatigue crack assessment method based on adaptive kernel density estimation assisted particle filter. Background technique [0002] The performance reliability of systems such as rotorcraft structures, which are riveted joints used in helicopter canopy covers, is usually affected by potential degradation mechanisms within the system, such as fatigue, wear, corrosion, etc., which eventually lead to System failure. Based on the historical degradation data of the system or the measured data of the degradation experiment, the degradation process of the system can be dynamically described by various models including random factors. With the advancement of sensor technology, the degradation state of the system in working state can be estimated by real-time monitoring of sensors. In recent years, this kind of degradation state assessment method based on degradation model...

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Problems solved by technology

[0007] The present invention aims at the defects in the above-mentioned prior art, and the purpose of the present invention is to propose a fusion adaptive kernel density estimation resampling improvement based on the particle shortage problem existing in the auxiliary particle filter method under the condition that the state noise has a large influence A Particle Filter-Assisted Method to Evaluate the Fatigue Crack State of Rotorcraft Structures

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