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Processing and Analysis on the GPR Image of Dam Hidden Hazard by Means of Artificial Neural Network

机译:大坝隐患GPR图像的人工神经网络处理与分析。

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The GPR effect of detecting dam hidden hazard relies on recognition of hidden hazard information in reflection image.The computing flow is introduced that processing GPR image by means of self-fitting ANN on MATLAB platform.Then the comparison results of practical GPR images between before and after processing using ANN are presented.The application results demonstrate that the hidden hazard information can be more obvious and the interpretation result can be more accurate through ANN method.And ANN method is able to improve the resolution of GPR image.The analysis result of practical image for one leak detection project is identical to that of the on-site excavation.And the grouting quantity for the interpreted non-uniform zone is more than that in other zone.So it welt helped the seepage treatment proiect.
机译:检测大坝隐患的GPR效果依赖于反射图像中隐患信息的识别,介绍了在MATLAB平台上通过自适应神经网络对GPR图像进行处理的计算流程,然后将实际GPR图像与之前的图像进行比较。应用结果表明,通过ANN方法可以使隐患信息更加明显,解释结果更加准确,而ANN方法可以提高GPR图像的分辨率。一个泄漏检测项目的图像与现场开挖的图像相同,并且解释的不均匀区域的注浆量大于其他区域的注浆量,因此它有助于渗流处理。

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