Open AccessNoise Analysis and Compensation Strategy of Photoelectric Detection Circuit
Author(s) -
Jiaqiong Qin,
Shaobo Cui,
Jun Dai
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1601/2/022047
Subject(s) - compensation (psychology) , photoelectric effect , interpolation (computer graphics) , computer science , adaptive neuro fuzzy inference system , noise (video) , linear interpolation , matlab , equivalent circuit , fuzzy logic , control theory (sociology) , algorithm , electronic engineering , artificial intelligence , fuzzy control system , engineering , pattern recognition (psychology) , optics , physics , electrical engineering , voltage , motion (physics) , psychology , control (management) , psychoanalysis , image (mathematics) , operating system
A photoelectric detection circuit was designed for improving the accuracy of photoelectric detection and reducing the system error. On the basis of analyzing the noise of the photoelectric detection circuit, the error compensation was proceeded on photoelectric detection circuit using lookup method, linear interpolation method, surface fitting method and adaptive neuro-fuzzy inference method, and the effects of the major error compensation method were compared. The measured data of photoelectric diode experimental platform was used as the sample data. The simulation results in the MATLAB environment demonstrate that under the same condition, the adaptive neuro-fuzzy inference method (ANFIS) can improve the detecting accuracy, and is more effective than lookup method, linear interpolation method, and surface fitting method.