Improving the subdivision accuracy of photoelectric encoder using particle swarm optimization algorithm

Abstract

To improve the subdivision accuracy of a photoelectric encoder and reduce the effects of sinusoidal errors in the signals on the measurement accuracy of the system, we designed an optoelectronic chip to receive grating moiré fringe signals. An amplifier circuit with a hierarchical pipelined architecture was designed, and the photodetector array was matched with the code disk before processing the received signals. Thereafter, a quantitative analysis was performed on the sinusoidal errors in the signals. From the analysis results, a sinusoidal error compensation method based on the particle swarm optimization (PSO) algorithm was developed, and a subdivision error compensation model was established to correct the errors in the signals. Finally, a fast solution for the PSO algorithm was implemented on a field-programmable gate array, and a grating test platform was built for experimental verifications. The results showed that the peak-topeak subdivision error of the encoder's photoelectric signal decreased by approximately 60% from 2.98ʺ to 1.13ʺ. Therefore, the scheme proposed in this paper is expected to significantly improve the measurement accuracies of photoelectric encoders.

Instantaneous grating signal subdivision system with non-linear Kalman filters

“…Therefore, it is necessary to introduce filtering algorithm to eliminate these interferences. At present, the commonly used denoising method are band-pass filters and mean filters [19][20][21][22][23][24][25][26]. However, as general filters, band-pass filter and mean filter do not consider the prior information that the grating encoder signal is sinusoidal, and thus do not achieve the best filtering result.…”