The benefits of Digital Twins are widely recognized across various use cases. However, to ensure efficient utilization of Digital Twins, it is crucial to minimize the effort required for their creation. This is particularly relevant for behavior models, which play a significant role in many Digital Twin use cases. While there are existing approaches for creating these models efficiently, they rely on having access to the asset's structure in a digitally usable format. This requirement also applies to the field of fluidics. The paper presents a method for the automated digitalization of information from fluid circuit diagrams, which contain information about the fluid structure of the asset. The method is implemented on the example of pneumatic vacuum ejectors, and using the test data set as an example, a large part of the information could be digitalized fully automatically. This was also demonstrated for an exemplary circuit diagram with poorer image quality.

中文翻译：

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流体回路图自动数字化的方法


数字孪生的优势在各种用例中得到了广泛认可。然而，为了确保数字孪生的有效利用，最大限度地减少创建数字孪生所需的工作量至关重要。这与行为模型尤其相关，行为模型在许多数字孪生用例中发挥着重要作用。虽然现有的方法可以有效地创建这些模型，但它们依赖于以数字可用格式访问资产的结构。这一要求也适用于流体学领域。本文提出了一种对流体回路图信息进行自动数字化的方法，其中包含有关资产流体结构的信息。该方法以气动真空发生器为例进行实施，以测试数据集为例，很大一部分信息可以完全自动数字化。对于图像质量较差的示例性电路图也证明了这一点。