Optimized geometric error sensitivity analysis approach based on stream-of-variation theory in multi-axis precise motion platform

Abstract

In this paper, an optimized error sensitivity analysis (ESA) approach based on stream-of-variation (SOV) theory in multi-axis precise motion platform (MPMP) is introduced. Unlike the conventional ESA method, this approach utilizes stream-of-variation theory to establish error model firstly. By regarding each axis as a station, the error propagation and deviation accumulation processes are clear station by station. Through obtaining the deviations after each station, the sensitive stations can be developed, and corresponding error terms are collected. Thus, by analyzing the appearance frequency of the errors, a precise sensitive order can be developed, and a sensitivity results with different steps is given. Through ignoring the insensitive and irrelevant errors, the computational volume of error model can be saved, and the efficiency can be improved. A case study about a typical MPMP used in laser welding system (LWS) is carried out, and the results indicate that the optimized ESA approach is more efficient and accurate, and it is flexible as well. This ESA approach is not only accurate in developing sensitive levels, but also balancing the systematic accuracy and working efficiency, which is helpful to provide informative guide to engineers.