Fatigue Fracture Reliability Analysis And Simulation Of The Driving System Of A Self-Propelled Gun

Fatigue lives prediction and reliability simulation of the driving system of a certain type of self-propelled gun are studied. This dissertation has provided these theoretic foundation and technical references for the maintenance guarantee of self-propelled guns. It is beneficial to improve guarantee capability and survivability of weapon equipments. A new set of CAE simulative method about fatigue fracture reliability analysis has been established. The random loading acting on the key components of the driving system have been obtained by simulating the virtual prototype of the self-propelled gun on various types of standard road. The scatters of all kinds of random factors are investigated based on fatigue fracture reliability theoretics. Furthermore, these calculation theoretics and simulation methods for crack initiation lives and crack propagation lives of the torsion shaft have been studied deeply from fatigue safe life/damage tolerance's view under multi-driving condition stochastic load.Firstly, the virtual driving experiment systems are built, which consist of the self-propelled gun virtual prototype using ATV (ADAMS/Tracked Vehicle), the numerical standard road surfaces and the contact models between the virtual prototype and the road surfaces. And the stochastic loading history of the key components of the driving system is simulated and obtained when the self-propelled gun drives in different speed grades on various types of standard road surfaces. The random loading has been counted, dealt with in statistics methods, synthesized and extended with these theories and methods, Which include the advanced rain-flow counting method, the weight coefficient method and the probability density — the steepest descent method. As a result, the 8 X 8 two-dimensional load design spectrum for the whole life was fulfilled.Secondly, this thesis has presented a fatigue reliability test simulation method of the structural detail to obtain the P-Sa-Sm-N fatigue surface. The random of these fatigue transverse factors has been considered, such as these correlative important sizes of the key components, the stress concentration factor K_f, the size correction factor ε and the surface quality correction factors β ,and so on. The effect of the scatter character of some critical sizes of the torsion shaft is investigated using the MENN (Modified Evolutionary Neural Network). The maximum shearing stress history of the critical location on the root of spline tooth obtained from results of simulation by MSC.Marc software is used for the MENN training samples. And the weight matrix and biases matrix of Neural Network is optimized and given by Genetic Algorithm simulation...