基于机器学习的钢轨表面缺陷分类识别
Classification and Identification of Rail Surface Defects Based on Machine Learning
庞少杰 1徐燕 1李双1
作者信息
- 1. 南通理工学院汽车工程学院,江苏 南通 226300
- 折叠
摘要
通过探讨一种基于机器学习的钢轨表面缺陷分类识别算法.该算法首先进行缺陷特征量的计算和提取,随后利用缺陷特征数据集对机器学习算法模型进行训练,最终利用训练好的算法模型对铁轨表面的缺陷进行识别和分类.
Abstract
An algorithm for classifying and identifying rail surface defects based on machine learning is explored.The algorithm firstly carries out the calculation and extraction of defective feature quantity,and then uses the defective feature dataset to train the machine learning algorithm model,and finally uses the trained algorithm model to identify and classify the defects on the rail surface.
关键词
机器学习/钢轨伤损检测/缺陷分类Key words
machine learning/rail injury detection/defect classification引用本文复制引用
基金项目
南通理工学院2023年江苏省大学生创新创业训练计划项目(202312056041Y)
出版年
2024
NETL
NSTL
万方数据