Design and Calibration of a Novel Angular Position Sensor Based on BP Neural Network

Bohan Lv, Zhenghao Zhang, Shan-chao Liu, Yuebo Zhong, Xinying Zhao
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Abstract

Based on the law of electromagnetic induction, a novel contactless absolute angular position micro-sensor has been designed in this paper. It is mainly composed of three parts: a magnet having two portions shaped as circle segments with different center points, a Hall effect sensor and a signal processing circuit. The linearity of the sensing system is improved by particularly designing spatial magnetic field distribution of asymmetric magnet, and Hall output signal is converted by the second-order low-pass filter circuit into linear analog voltage. Experiment has been performed on a prototype of the angular position sensor and the results demonstrate the proposed scheme is feasible. Theoretic precision and testing error analysis of the sensor has been pursued based on BP neural network at the end of the paper. The error does not exceed ± 0.015°. The prediction result can fully reproduce the output performance of hall sensing system with high accuracy of 0.02%, achieving high-precision angle measurement.
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基于BP神经网络的角位置传感器设计与标定
基于电磁感应原理,设计了一种新型的非接触式绝对角位置微传感器。它主要由三部分组成:具有两部分形状为圆心不同的圆段的磁铁、霍尔效应传感器和信号处理电路。通过特别设计不对称磁体的空间磁场分布,提高了传感系统的线性度,并通过二阶低通滤波电路将霍尔输出信号转换成线性模拟电压。在角位置传感器样机上进行了实验,结果表明该方案是可行的。最后对传感器进行了基于BP神经网络的理论精度和测试误差分析。误差不超过±0.015°。预测结果可以完全再现霍尔传感系统的输出性能,精度达到0.02%,实现高精度角度测量。
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