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Methods of diagnostic of pipe mechanical damage using functional analysis, neural networks and method of finite elements

机译:使用功能分析,神经网络和有限元方法诊断管道机械损伤的方法

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The main goal of the study is to analyze methods and diagnose mechanical damage to the pipeline using functional analysis, neural networks and the finite element method. In the work, mathematical formulations of the corresponding geometrical inverse problems of the theory of shells on reconstruction of defects of lateral surface are formulated according to measurement data obtained from sensors located in a given section of the shell. The statement was given and a method for solving inverse geometric problems for a shell of Tymoshenko type was developed. The authors have offered methods for solving inverse geometric problems of identifying volumetric and crack-like defects in extended underground structures and pipelines based on the analysis of responses to unsteady elastic-wave perturbations using the mathematical apparatus of wavelet signal transformation, the finite element modeling method and intelligent software system based on neural network.
机译:该研究的主要目标是使用功能分析,神经网络和有限元方法分析方法并诊断对管道的机械损坏。在作品中,根据从位于壳体的给定部分中的传感器获得的测量数据配制了横向表面缺陷的壳体的重建的相应几何逆问题的数学制片。发表了陈述,并且开发了一种解决Tymoshenko类型壳体逆几何问题的方法。作者提供了用于在使用小波信号变换的数学仪器的响应的分析,提供了对延伸的地下结构和管道中的延伸地下结构和管道中识别体积和裂纹状缺陷的逆几何问题的方法,是使用小波信号变换的数学仪器,有限元建模方法基于神经网络的智能软件系统。

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