Fatigue crack assessment method based on adaptive kernel density estimation auxiliary particle filtering

Abstract

The invention provides a fatigue crack assessment method based on adaptive kernel density estimation auxiliary particle filtering. The method comprises the following steps of: determining a key assessment part, constructing a state equation and an observation equation of the fatigue crack random expansion model; and constructing a nonlinear state space model to describe an evaluation process of fatigue crack propagation, and performing simulation calculation of a crack propagation state on the nonlinear state space model of fatigue crack propagation of the rotorcraft structure based on a self-adaptive kernel density estimation auxiliary particle filtering method. The invention corrects a re-sampling step by using a kernel density estimation method under the condition that a state model isuncertain, so that the resampled particles maintain diversity and improve the accuracy of the filtering estimation result. An adaptive kernel bandwidth selection scheme is proposed by using particle weights to obtain better kernel density estimation results and applied to the particle filter framework. The estimation accuracy of fatigue crack propagation is improved, and the safety of the rotorcraft structure is improved.

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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