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A fuzzy inference system for two-phase flow regime identification from radiography images

机译:射线图像两相流态识别的模糊推理系统

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摘要

Swiftly identifying the two-phase flow that occurs in coolant channels is crucial for monitoring energy producing installations such as boiling water reactors. In this piece of research, a Sugeno-type fuzzy inference system is implemented for online, non-invasive flow regime identification. The proposed system is predominantly efficient in its construction and operation: a single directly computable input is employed and as many fuzzy inference outputs and rules are used as there are flow regimes to be identified. Non-invasiveness is accomplished through the utilisation of radiography images. Compactness notwithstanding, the fuzzy inference system successfully and reliably identifies the flow regime of sequences of frames from neutron radiography videos.
机译:快速识别在冷却剂通道中发生的两相流对于监控诸如沸水反应堆之类的发电设备至关重要。在这项研究中,实现了Sugeno型模糊推理系统,用于在线,无创流动状态识别。所提出的系统在构造和操作方面非常有效:采用单个可直接计算的输入,并且使用了许多模糊推理输出和规则,因为要确定流态。通过使用放射线照相图像来实现非侵入性。尽管具有紧凑性,但模糊推理系统仍可成功可靠地从中子射线照相视频中识别出帧序列的流态。

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