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中文摘要：
基于电容层析成像（ECT）和人工神经网络的软测量方法,实现了两相流流型识别。以油气两相流为例,建立了两相流流型识别的软测量模型。从ECT传感器的输出中提取特征参数作为软测量模型的辅助变量,两相流流型为主导变量,构建二级自组织竞争神经网络,进而实现对两相流流型的在线判别。仿真结果表明,该方法判别精度高、判别速度快。
英文摘要：
Taking the oil-gas two-phase flow as an example, this paper investigated the identification of flow regimes using soft-sensing technique, which is based on Electrical capacitance tomography （ECT） and artificial neural network. An online soft-sensing model was built. The character parameters extracted from ECT sensor outputs were the second variable. The primary variable was flow regime of oil-gas two-phase flow. Then, a two- layer self-organizing competitive neural network was built. Simulation results showed that the proposed method has good identification precision and fast identification speed, which means it is an effective tool in two-phase flow pattern online identification.
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Preliminary Simulations on Magnetic Induction Tomography of the Brain Based on Finite Element Method
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