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Compensation of Rotary Encoders Using Fourier Expansion-Back Propagation Neural Network Optimized by Genetic

Hua-Kun Jia1, Lian-Dong Yu1, Yi-Zhou Jiang1

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Summary

This study introduces a novel Fourier expansion-back propagation (BP) neural network optimized by genetic algorithm (FE-GABPNN) to enhance rotary encoder accuracy. The method significantly reduces angle measurement errors caused by ambient temperature variations in precision instruments.

Keywords:
BP neural networkangle measurement errorgenetic algorithminstrumentrotary encodertemperature compensation

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Area of Science:

  • Metrology
  • Instrumentation
  • Mechanical Engineering

Background:

  • Rotary encoders are crucial for measurement accuracy in precision instruments with rotation joints.
  • Ambient temperature variations and manufacturing imperfections can introduce significant angle measurement errors in rotary encoders.

Purpose of the Study:

  • To propose and validate a novel method for improving the angle measurement accuracy of rotary encoders.
  • To compensate for angle measurement errors caused by ambient temperature fluctuations.

Main Methods:

  • Development of a Fourier expansion-back propagation (BP) neural network optimized by a genetic algorithm (FE-GABPNN).
  • Integration of Fourier expansion characteristics, BP neural network, and genetic algorithm for error compensation.
  • Calibration of a rotary encoder in an articulated coordinate measuring machine (ACMM) using an autocollimator and optical polygon across a temperature range of 10–40 °C.

Main Results:

  • The FE-GABPNN method demonstrated good fitting performance.
  • Angle measurement errors were significantly reduced from 110.2″ to 2.7″ after compensation.
  • The mean root mean square error (RMSE) of residual errors was 0.85″.

Conclusions:

  • The proposed FE-GABPNN method effectively improves the angle measurement accuracy of rotary encoders.
  • This approach offers a robust solution for compensating temperature-induced errors in precision measurement systems.
  • The method shows significant potential for applications in high-precision metrology and instrumentation.