Unmanned vehicle structure damage tracking and fatigue estimating method

Abstract

The invention provides an unmanned vehicle structure damage tracking and fatigue estimating method. The unmanned vehicle structure damage tracking and fatigue estimating method comprises the steps that 1, collecting the load-time history at the joint of the structure part of the unmanned vehicle ; 2, according to the the load-time history at the joint of the structure part, carrying out, using damage mechanics-definite element solution to calculate damage degrees of all units of the structural part, and further comprising the following steps: step 21, calculating the damage degree of each unitof the structural member according to the load-time journey; According to the time history, solving a strain field of the structure under the initial damage degree D0 through a finite element method,and solving damage mechanics and other effect variations; Step 22: obtaining a damage degree increment dD under a given step length dN according to a damage evolution equation in a strain form, and accumulating the damage degree D = D0 + dD; wherein The cumulative load cycle number is N = N0 + dN; And 23, breaking the elastic model of the material, ED = E (1-D), repeating the steps 21 and 22 until the damage degree D of a certain unit reaches 1 wherein the number of output load cycles is the crack initiation life. According to the invention, the damage evolution process of each part of the unmanned vehicle structure can be monitored in real time, and the fatigue life of each part is estimated.

Description

technical field [0001] The invention relates to finite element technology, damage mechanics method and data fusion technology, in particular to a method for remote damage tracking and fatigue life estimation of unmanned vehicle structural parts (key stress parts). Background technique [0002] With the advent of the era of artificial intelligence, unmanned driving technology is booming, and unmanned vehicles are gradually appearing in parks, communities, patrols and other scenarios. At present, people's attention to the safety performance of unmanned vehicles is mainly focused on sensors, obstacle recognition, path planning algorithms, etc., but at the same time, a certain amount of attention should be paid to the safety performance of key components such as brake pads and traditional systems. For unmanned systems, real-time tracking and monitoring of damage to key structures under stress is also an important supplement to the security of unmanned systems. [0003] Structur...

AI Technical Summary

Problems solved by technology

At present, the nominal stress-strain method or local stress-strain method is generally used to estimate the crack initiation life, which cannot track the damage of structural parts in real time, and has the disadvantages of high calculation cost and poor calculation accuracy; in addition, the traditional fatigue method is based on linear damage accumulation. , and only focus on the stress concentration point of the structure, but the actual situation is that the cumulative damage is highly nonlinear with the service life, and with the replacement of parts, the stress is redistributed, the traditional fatigue method cannot predict the damage of other parts of the structure, and it is difficult to do a second fatigue prediction

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