Research of nonlinear correction method in shafting alignment test system based on PSD

LI Bo，GAO Yi， CAO Guo-hua， LIU Chang-qing
（College of Mechatronic Engineering， Changchun University of Science and Technology， Changchun 130022， China）

Abstract： Aiming at the large nonlinear error of position sensitive detector（PSD），which is the core device of shafting alignment test system，output coordinate of PSD cannot correctly reflect the actual location of the incident light point， in order to improve the alignment test accuracy，the online calibration device based on the PI micro displacement platform was designed，the nonlinear correction algorithm based on BP neural network was presented，the data acquisition and nonlinear correction experiment was proceeded，acquired data and corrected data were simulated and analyzed by Matlab，respectively. The results indicate that the algorithm based on BP neural network is practical and efficient，after correction using this algorithm by the linearity error of PSD is less than 3.9 μm. The influence of nonlinear is largely reduced，so that the linearity and the data confidence of B area are greatly improved. On the premise of not increasing the cost and device complexity，the accuracy of the entire alignment system are effectively increased.
Key words： 2D-position sensitive detector（PSD）； nonlinear correction； artificial neural network； micro displacement platform