Research on Reliability of Positioning Accuracy of Electromechanical Coupling Ammunition Loading Manipulator During Rotation Process

Abstract

The loading manipulator is an important actuator in modern artillery automatic loading systems, and it is crucial to evaluate its positioning accuracy accurately and efficiently. This paper presents a reliability analysis method based on the combination of feedforward neural network (FNN) and mixed importance sampling (MIS) to study the positioning accuracy of the loading manipulator. First, the manipulator dynamic model considering the control system is established. To improve the efficiency of reliability analysis, a surrogate model based on FNN is constructed. By searching the most probable point (MPP) of each limit state equation, an MIS density function is constructed, after which important samples can be extracted to evaluate the reliability of the positioning accuracy of the manipulator. Compared with the Monte Carlo simulation (MCS) method, the proposed method enjoys higher efficiency while ensuring accuracy. The results of the example show that the gear clearance and friction coefficient have an important effect on the positioning accuracy of the loading manipulator, which should be taken into account in the machining and installation process.