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Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network

机译:基于改进BP人工神经网络的罐底腐蚀状态智能评价方法

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According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status are confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information, and online testing information are established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information is 94 %. The evaluation model can evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.
机译:根据声发射信息和坦克底部在线测试的外观检测信息,确认了与罐底腐蚀状态相关的外部因素。建立了应用人工神经网络智能评估方法,建立了三个基于外观检测信息,声发射信息和在线测试信息的三个罐底腐蚀状态评估模型。与通过评估测试样本的声发射在线测试的结果进行比较,基于在线测试信息的评估模型的准确性为94%。评估模型可以准确评估坦克底部腐蚀,并实现坦克底部的声学在线测试智能评估。

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