Uncertainty Quantification of Vector Nozzle Mechanism Through a Data-Driven Approach

The vector nozzle will inevitably produce uncertain joint clearance during the manufacturing, assembly and working processes. The kinematic accuracy and dynamic response of the vector nozzle mechanism will be affected by the uncertainty of joint clearance. The joint clearance uncertainty causes the strong nonlinearity of the vector nozzle mechanism. This paper proposes an analysis method for the kinematic accuracy and dynamic response of the rigid-flexible coupling vector nozzle mechanism with uncertain joint clearance based on the deep neural network. The uncertainty analysis process based on the deep neural network model and Latin hypercubic sampling method is given to illustrate the relationship between the joint clearance and the dynamic response of the nozzle mechanism. The results show that the uncertainty of joint clearance should be considered for the rigid-flexible coupling vector nozzle mechanism in order to accurately assess its performance and to provide a reference for the design, analysis and assessment of the vector nozzle mechanism.