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Simulation on the Performance of Ceramic-Lined Steel Pipe Prepared by SHS Process Based on Artificial Neural Network

机译:基于人工神经网络的SHS工艺制备的陶瓷内衬钢管性能模拟

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In order to study the relationship between reaction recipe and the performance of ceramic-lined steel pipe prepared by SHS process, 21 groups data obtained in the experiment were used. the different reaction recipes were taken as input data. Besides, the crushing strength and the density of ceramic layer were taken as output data. the BP neural network model was established to simulate the performance of ceramic lined composite steel pipe under different reaction recipes. Simulation results show that: the use of BP neural network simulation of ceramic lined composite tube crushing strength and the density of the steel pipe ceramic layer maximum error of 2.6742% and 4.8445%.It meets the needs in the engineering.
机译:为了研究反应配方与通过SHS工艺制备的陶瓷衬里钢管的性能之间的关系,使用了实验中获得的21组数据。将不同的反应配方作为输入数据。此外,将陶瓷层的抗压强度和密度作为输出数据。建立了BP神经网络模型,以模拟陶瓷衬里复合钢管在不同反应配方下的性能。仿真结果表明:利用BP神经网络对内衬陶瓷复合管的抗压强度和钢管陶瓷层密度的模拟最大误差分别为2.6742%和4.8445%,满足了工程需要。

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