Loading cabin door intensity analysis based on unmanned plane

Abstract

The invention discloses loading cabin door intensity analysis based on an unmanned plane. The loading cabin door intensity analysis is characterized by comprising the following steps: 1, analyzing loading cabin door finite element strength, performing geometric description on a composite material structure serving as an analysis object, building a loading cabin door finite element model, performing loading cabin door finite element strength analysis, and measuring acceleration information of a real wing and an acceleration and strain information of a key point on an airplane body; 2, storing a loading cabin door finite element strength analysis structure in the form of a vector, storing and displaying displacement and stress results of all nodes obtained by loading cabin door stress analysis in the form of a displacement field and a force field of a vector form, taking the measured acceleration information of the wing as outer load input information of a simulation model, and simulating the acceleration and a strain result of the key point of the airplane body; 3, building a finite element model for a sliding door joint to perform mesh refinement on an important part.

Description

technical field [0001] The invention relates to a strength analysis of a load hatch, in particular to a strength analysis of a load hatch based on an unmanned aerial vehicle Background technique [0002] The structural reliability of the whole machine and parts of UAV is a matter of great concern to UAV manufacturers and users, and the road reliability test is an important means to investigate the reliability of the whole machine and parts. In terms of reliability test, three types of tests are generally carried out: actual road test; proving ground test; indoor bench test. The actual road test period is too long, the test field test period is long and the repeatability is poor, and the indoor bench test period is short and repeatable but the equipment is expensive. The load on the UAV load hatch is a dynamic load that changes with time, most of which are cyclic random loads, and the dynamic load will cause dynamic stress on many components on the UAV, and eventually lead t...

AI Technical Summary

Problems solved by technology

The actual road test period is too long, the test field test period is long and the repeatability is poor, and the indoor bench test period is short and the repeatability is high, but the equipment is expensive

The load on the UAV load hatch is a dynamic load that changes with time, most of which are cyclic random loads, and the dynamic load will cause dynamic stress on many components on the UAV, eventually leading to fatigue damage of parts

There are two ways to measure the driving load of the drone: one is to measure the local stress and strain. This method directly arranges strain gauges at the high stress and strain points of the parts. The measurement results can be directly used for the calculation of fatigue damage, but the results cannot be converted to other parts

The second is to measure the external load of the UAV. This method generally uses wing sensors to measure the load acting on the wing, but it is more complicated and costly

The static strength analysis of the composite material structure of the load hatch of the UAV is mainly carried out in two ways: one is the combination of coarse mesh finite element model analysis and local strength check, this analysis mode will cause inaccurate detail strength analysis , relying on a large number of experimental verifications, and sometimes performing local structure fine mesh finite element analysis, but the boundary of the local model is basically fixed or simply supported, which cannot reflect the elastic support state of the real structure

The second is to use fine grids for overall stress finite element analysis. This method is fine for uncomplicated small structures, but for large and complex UAV structures, the number of finite element model units and nodes is huge, and it is difficult for computers to run , nonlinear analysis and optimization analysis cannot run at all, and it is difficult to obtain the stress distribution of key attention parts