基于机器学习的工件合格分类

Classifi cation of Workpiece Qualifi cation Based on Machine Learning

随着自动化程度越来越高,越来越多的工厂配置了自动化的生产流水线。那么在无人的生产流水线上,非常重要的一个环节就是在生产的工件出厂之前进行相应的合格检验,就是判断一个工件是否符合出厂的标准。在以往对于工件的判断往往需要人工去逐个判断工件是否出厂的标准。由于人体力和精力有限,所以往往会有不合格的产品出厂。本文利用机器学习中的相应分类算法,对要出厂的工件进行相应的分类判断,实现自动化流水线上的最后一环不会有不合格品流出。

With the increasing degree of automation,more and more factories have been equipped with automated production lines.In the production line of no one,one of the most important links is to carry out the corresponding conformity inspection before the work piece is manufactured,which is to judge whether a work piece is in conformity with the factory standard.In the past,it is often necessary to manually judge whether the work piece is factory-made or not.Due to the limited physical and physical strength of the human body,there is often an unqualifi ed product.This paper makes use of the corresponding classifi cation algorithm in the machine learning to make the corresponding classification and judgment on the work pieces to be delivered,so as to realize the final part of the automatic production line and not to fl ow out of the non-conforming products.