@inproceedings{c075037bd4bd472da52f9081b887138b,
title = "The application of machine vision in inspecting position-control accuracy of motor control systems",
abstract = "In this paper, a new structured-light machine vision technique based on a radial basis function (RBF) neural network is proposed and an inspection system is established. General structured-light machine vision techniques are usually based on accurate mathematical models and have some unavoidable and inexpressible errors. The proposed new technique is based on the training and learning of high-accuracy samples and overcomes the disadvantages of the general technique and considerably improves the accuracy of machine vision inspection systems. An experiment applying this new technique to inspect the position-control accuracy of a step-motor controlled stage with one linear translation axis shows that the RBF artificial neural network (ANN) is quite suited to structured-light machine vision inspection systems and that structured-light machine vision inspection techniques are really a novel and effective means for the inspection of the position-control accuracy of motor control systems.",
keywords = "Accuracy, RBF neural network, machine vision, motor control systems, structured-light",
author = "Zhenzhong Wei and Guangjun Zhang and Xin Li",
note = "Publisher Copyright: {\textcopyright} 2001 Int. Acad. Publ./World Publ. Corp.; 5th International Conference on Electrical Machines and Systems, ICEMS 2001 ; Conference date: 18-08-2001 Through 20-08-2001",
year = "2001",
doi = "10.1109/ICEMS.2001.971794",
language = "英语",
series = "ICEMS 2001 - Proceedings of the 5th International Conference on Electrical Machines and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "787--790",
editor = "Wang Fengxiang and Tang Renyuan",
booktitle = "ICEMS 2001 - Proceedings of the 5th International Conference on Electrical Machines and Systems",
address = "美国",
}