Improved particle swarm optimization applied in calibrating a three-axis measuring system

In this paper, three-axis measuring system calibration problems, according to the ideal measurement system projection orthogonal system of thought, through the vector field measurement system to map the relationship between ideal orthogonal system, establish measurement system deviation parameter model; PSO algorithm will introduce self-learning mechanism and thus solve the optimal mapping parameters, the measurement system quadrature error between axes, as well as gain deviation between axes simultaneously zero drift is corrected to achieve a measurement system to map the relationship between ideal orthogonal system parameter identification. Simulation results show that this method can be very effective in achieving an effective measurement system for three-axis correction.