| 基于Online LS-SVM的钢铁件淬火硬度在线检测 |
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| 引用本文： | 贾健明,颜鹏. 基于Online LS-SVM的钢铁件淬火硬度在线检测[J]. 电子测量技术, 2009, 32(3): 68-71 |
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| 作者姓名： | 贾健明 颜鹏 |
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| 作者单位： | 常州信息职业技术学院机电工程系,常州,213164;常州信息职业技术学院机电工程系,常州,213164 |
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| 基金项目： | 江苏省高校自然科学研究指导性计划研究项目，江苏省高校高新技术产业发展指导性计划项目，江苏省常州市工业科技攻关计划 |
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| 摘 要： | 为了实现钢铁件淬火硬度的在线电磁无损检测,提出了在线最小二乘支持向量机（online least square support vector machine）的建模方法。Online LS-SVM是以增量学习训练SVM,以减量学习减少样本数,实现小样本估计的训练方法。实验结果表明,Online LS-SVM不仅能实现钢铁件淬火硬度的在线电磁无损检测,而且具有学习速度快,泛化性能好,对样本依赖程度低的优点。
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| 关 键 词： | 最小二乘支持向量机 人工神经网络 在线检测 电磁无损检测 硬度 |
Online ENDT for hardness of iron and steel parts based on online LS-SVM |
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| Jia Jianming,Yan Peng. Online ENDT for hardness of iron and steel parts based on online LS-SVM[J]. Electronic Measurement Technology, 2009, 32(3): 68-71 |
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| Authors: | Jia Jianming Yan Peng |
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| Affiliation: | Dept.of Mechanical and Electrical Engineering;Changzhou College of Information Technology;Changzhou 213164 |
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| Abstract: | On the purpose of realizing the online electromagnetic nondestructive testing(ENDT) for hardness of iron and steel parts,a novel method of Online LS-SVM(Online Least Square Support Vector Machine)was proposed.Online LS-SVM means that LS-SVM can be trained in an incremental way,and can be pruned to get sparse approximating in a decremental way.The experiments show that this method not only achieves the online ENDT for hardness of iron and steel parts,but also have many advantages such as high learning speed,... |
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| Keywords: | LS-SVM artificial neural network （ANN） online detecting electromagnetic nondestructive testing （ENDT） hardness |
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