一种基于BP神经网络测量物体高度的快速方法

A Fast Method for Measuring Objects' Height Based on BP Neural Network

本文提出的方法是在相位测量法的基础上,利用神经网络建立折叠相位与高度的映射关系,不需要严格搭建系统,也不需要展开相位及标定系统,不必考虑由系统的非线性所带来的误差。测量结果的精度在十个微米左右,标准方差在一个微米以下,是一种快速有效且准确稳定的机器视觉高度测量方法。

In this paper, a new effective and simple machine vision measuring method is proposed. This method aims at solving a problem that the central position of laser can hardly be extracted accurately in the methods for measuring objects' height based on line structured light. This method can slove objects' phase by means of phase measuring profilometry, and build a nonlinear map between phase of structured light and height based on self-recall function of artificial neural network. Then the information of objects' height can be obtained so long as the phases of objects are known. Its accuracy is about ten microns.