使用改进型BP神经网络量化裂纹漏磁信号

基金项目:

国家高技术发展研究计划(863)资助项目(2007AA06Z223)

详细信息

Characterizing Magnetic Flux Leakage Signal of Cracks Based on Improved BP Neural Network

摘要: 为量化油气管道的裂纹漏磁信号, 提出使用改进型BP神经网络的方法。介绍了BP神经网络的运作方式、改进的BP算法和如何将遗传算法用于改进BP神经网络的初始权值和阈值。测试样本和实际检测数据的输出结果表明, 采用改进型BP神经网络量化裂纹漏磁信号是可行的。
- 漏磁检测 /
- 信号处理 /
- 裂纹量化 /
- BP神经网络 /
- 遗传算法
Abstract: An improved BP neural network was proposed to characterize magnetic flux leakage signal of cracks in pipeline. The artificial neural network in simplicity, ways to improve BP(back propagation) algorithm, and usage of genetic algorithm to adjust parameters of BP neural network were introduced. Experimental results were presented and demonstrated the effectiveness of this method.
- Magnetic flux leakage testing /
- Signal processing /
- Crack quantification /
- BP neural network /
- Genetic algorithm

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