The Method Used for Process Precision Prediction of Micro-Assembly Based on Principle of Maximum Entropy

Abstract

This paper briefly introduces the principle of sub-micro precision micro-assembly system based on the micro force detection. The linear mapping of micro force-micro displacement can be obtained, which is in agreement with the experimental data. And the probability distribution density function of the fitted mapping coefficients can be derived by the principle of maximum entropy. Furthermore, the uncertainly of k is accessed. Hence, the reliability of micro force-micro displacement mapping in the assembly process is demonstrated. The experiment result shows that the assembly precision can be accurately predicted by the fitted micro force-micro displacement mapping.

Prediction of Array Antenna Assembly Accuracy Based on Auto-Encoder and Boosting-OSKELM

“…In order to study the effect of assembly error on the antenna gain, Guo et al [1] proposed an accurate gain prediction model using an improved XGBoost algorithm and the transfer learning method, based on the simulation data and experience. Combined with the principle of maximum entropy, Zhang et al [2] proposed the probability density function model of the relationship between micro force and displacement, which can promote process accuracy prediction of micro-assembly. Mu et al [3] studied the construction method of •3• composite processing components considering the manufacturing error and deformation factors of parts, and proposed a new prediction method of aero-engine high-pressure rotor system.…”