High-precision Adaptive Photoelectric Encoder Using Triple Image Sensors in 120° Symmetric Layout

The escalating demand for angular measurement precision in industrial automation and precision manufacturing has driven significant research into image-based photoelectric encoders, valued for their noncontact operation and high-resolution capabilities.In this study, we present a self-adaptive angular displacement measurement model utilizing triple image sensors to mitigate pronounced even-order harmonic errors and inadequate environmental susceptibility in conventional single/dual-sensor systems.The proposed design integrates a 120° symmetric configuration with a hybrid "mechanical calibration-algorithmic compensation-environmental adaptation" strategy, enhanced by extended Kalman filter (EKF) bias estimation and gradient descent weight optimization.Simulation and experimental results demonstrate that the triplesensor system reduces the second harmonic component ratio from 2.1% (dual-sensor baseline) to 0.6%, achieving 71% harmonic suppression.Static repeatability improves by 65% (±1.2″ vs ±3.5″), while dynamic interpolation error decreases by 66% (±1.2″ vs ±3.5″).Environmental robustness tests reveal an 80% reduction in temperature drift coefficient (±0.5″/°C vs ±2.5″/°C) and an 8 dB enhancement in vibration noise rejection (50 dB vs 42 dB).The system maintains ±1.8″ accuracy under single-point failure.Through nanoimprinted gratings and 3D stacked packaging, a 40% reduction in system volume and a 30% lower power consumption are achieved, compared with conventional implementations.This work provides both theoretical and practical foundations for high-precision photoelectric encoder engineering.