首页> 外文会议>International Conference on Natural Computation;ICNC '09 >Research on Magnetic Flux Leakage Signals Quantity Technology of Tank Floor Corrosion Defects Based on Artificial Neural Network
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Research on Magnetic Flux Leakage Signals Quantity Technology of Tank Floor Corrosion Defects Based on Artificial Neural Network

机译:基于人工神经网络的油罐底板腐蚀缺陷磁通量泄漏信号量化技术研究

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Magnetic flux leakage testing method is a major direction of tank floor testing. In this paper, the spatial distribution of magnetic flux leakage field of tank floor corrosion defects is analyzed based on the features of magnetic flux leakage signals. BP neural network model is applied to the quantity analysis of tank floor corrosion defects. The results in network training and test reach the quantitative accuracy requirements of tank floor corrosion defects, the established BP neural network is effective to the quantitative recognition of depth and width of the defects.
机译:漏磁测试方法是储罐底板测试的主要方向。本文基于漏磁信号的特征,分析了罐底腐蚀缺陷漏磁通的空间分布。 BP神经网络模型被应用于罐底腐蚀缺陷的数量分析。网络训练和测试结果达到了罐底腐蚀缺陷的定量精度要求,所建立的BP神经网络对缺陷深度和宽度的定量识别是有效的。

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