流型是流体在管道中流动时，呈现的不同形态或流动模式。根据流体数量的多少可分为两相流和多相流。
这是一个流型识别项目，旨在利用深度学习等人工智能技术区分不同流型。尤其是帮助发现段塞流、环状流等恶劣流型，及时采取相应措施，以预防管道系统故障，减少损失。本项目提出YOLOv8_1D模型和YI-Net模型，可以实现实时流型识别。为流型识别领域，提供了新的解决方案。
Flow pattern refers to the different forms that a fluid presents when flowing in a pipeline. According to the number of fluid, it can be divided into two-phase flow and multiphase flow.
This is a flow pattern identification project aimed at using artificial intelligence technologies such as deep learning to distinguish different flow patterns. Especially to help identify hazardous flow patterns such as slug flow and annular flow, and take corresponding measures in a timely manner to prevent pipeline system failures and reduce losses. This project proposes the YOLOv8_1D model and YI-Net model, which can achieve real-time flow pattern identification. Provided a new solution for the field of flow pattern identification.
目前，通过改进YOLOv8分类网络和YOLOv10相关模块，提出YOLOv8_1D和YI-Netv1。
At present, YOLOv8_1D and YI-Netv1 have been proposed by improving the YOLOv8 classification network and YOLOv10 related modules.
由于采集的管道压力是一维数据。为了保证实时性并实现模型维度与数据维度的匹配，将YOLOv8分类网络一维化并调整卷积核尺寸，得到YOLOv8_1D模型。
Due to the fact that the collected pipeline pressure is one-dimensional data. In order to ensure real-time performance and match the model dimension with the data dimension, the YOLOv8 classification network is transformed into one-dimensional and the convolution kernel size is adjusted to obtain the YOLOv8_1D model.
为了进一步降低YOLOv8_1D的参数量，将YOLOv10提出的SCDown模块一维化为SCDown1d，用此模块代替YOLOv8_1D配置文件中的后两个卷积Conv1d。
为了减少YOLOv8_1D的冗余计算，将YOLOv10提出的CIB模块一维化为CIB1d，并用CIB1d取代C2f1d的Bottleneck层，得到C2fCIB1d模块，用此模块代替YOLOv8_1D配置文件的最后一个C2f1d。
最终得到新型一维模型，命名为YI-Net，全称为 “One-dimensional Intelligent Network”，即“一维智能网络”。
这是YI-Net网络的第一个版本，记为YI-Netv1。
In order to further reduce the parameter count of YOLOv8_1D, the SCDown module proposed by YOLOv10 is transformed into one-dimensional called SCDown1d, which replaces the last two convolution Conv1d in the YOLOv8_1D configuration file.
In order to reduce redundant calculations in YOLOv8_1D, the CIB module proposed by YOLOv10 is transformed into one-dimensional called CIB1d, and the Bottleneck layer of C2f1d is replaced by CIB1d to obtain the C2fCIB1d module, which replaces the last C2f1d in the YOLOv8_1D configuration file.
Finally, a new one-dimensional model was obtained and named YI-Net, which full name is "One-dimensional Intelligent Network".
This is the first version of the YI-Net network, denoted as YI-Netv1.
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