Abstract
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.
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Acknowledgment
This work was supported in part by China national petroleum corporation science and technology development projects under Grant No. 2011D-4603-0101.
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© 2015 Springer Science+Business Media New York
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Qiu, F., Dai, G., Zhang, Y. (2015). Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network. In: Shen, G., Wu, Z., Zhang, J. (eds) Advances in Acoustic Emission Technology. Springer Proceedings in Physics, vol 158. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1239-1_13
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DOI: https://doi.org/10.1007/978-1-4939-1239-1_13
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