| 多层BP神经网络在钢铁材质裂纹检测中的应用 |
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| 引用本文： | 盛永生,何云斌.多层BP神经网络在钢铁材质裂纹检测中的应用[J].齐齐哈尔轻工业学院学报,2011(3):7-9. |
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| 作者姓名： | 盛永生 何云斌 |
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| 作者单位： | [1]哈尔滨理工大学科学技术系,哈尔滨150080 [2]黑龙江八一农垦大学,黑龙江大庆163319 |
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| 摘 要： | 用设计好的电磁检测设备测得长螺栓的初始磁导率后,对所获得的模拟数据进行数字化处理得到磁导率特征值。设计了多层BP神经网络对钢铁材质长螺栓进行裂纹检测,实验数据表明,分类算法实现简单、分类准确,较容易应用在钢铁材质无损检测的实时系统中。
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| 关 键 词： | 初始磁导率 多层BP神经网络 裂纹检测 |
Application of multilayer BP neural network for crack detecting to steel material |
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| Authors: | SHENG Yong-sheng HE Yun-bin |
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| Affiliation: | 1.Harbin University of Science and Technology Harbin 150080,China; 2.Heilongjiang Bayi Agriculture University,Heilongjiang Daqing 163319,China) |
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| Abstract: | After detected initial permeability curve line by electromagnetic testing device that is designed,eigenvalue of initial permeability is achieved by digital signal processing method appling to analog data.A multilayer BP neural network is designed to classify queen bolt,it can solve the problem of crack detecting efficiently.The implementation of classification algorithm is simple,classifying exactly and is very easily to apply to real-time system of crack detecting. |
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| Keywords: | initialpermeability multilayer BP neural network crack detecting |
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