Abstract Oscillatory two-phase flow as a common two-phase flow occurs extensively within the engine's thermal management system. However, it is found that the oscillatory two-phase flow patterns at the same location have different flow states caused by the strong turbulence under fast moving speed conditions, making it difficult to propose systematic identification and judgement criteria. Common image processing methods applied to tube flow are unsuitable for the analysis of oscillatory two-phase flow with particularly complex flow patterns. To solve this problem, this paper presents a study aiming to determine common rules from the instantaneous flow patterns by eliminating the random variability and making the oscillatory two-phase flow pattern images more representative. Applying the phase-averaged pre-processing and textural feature method to the instantaneous oscillatory two-phase flow patterns, which are captured by the designed visualized test bench, the lowest identification results based on the Support Vector Machine (SVM) could achieve an accuracy of 92.5%. The results suggest that the study presented in this paper offers an effective method for the analysis and identification of oscillatory two-phase flow patterns. Visualized experimental results in the related fields of two-phase flow will be more comprehensive with objective descriptions and representative flow pattern images.

中文翻译：

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相位平均预处理方法在基于纹理特征的振荡两相流型识别中的应用

摘要 振荡两相流作为一种常见的两相流广泛发生在发动机的热管理系统中。然而，发现同一位置的振荡两相流型在快速移动速度条件下由于强烈湍流而具有不同的流动状态，因此难以提出系统的识别和判断标准。应用于管流的常见图像处理方法不适用于分析具有特别复杂流动模式的振荡两相流。为了解决这个问题，本文提出了一项研究，旨在通过消除随机变化并使振荡两相流型图像更具代表性，从瞬时流型中确定共同规则。将相位平均预处理和纹理特征方法应用于设计的可视化测试台捕获的瞬时振荡两相流模式，基于支持向量机（SVM）的最低识别结果可以达到92.5%。结果表明，本文提出的研究为分析和识别振荡两相流型提供了一种有效的方法。两相流相关领域的可视化实验结果将更加全面，具有客观的描述和代表性的流型图像。结果表明，本文提出的研究为分析和识别振荡两相流型提供了一种有效的方法。两相流相关领域的可视化实验结果将更加全面，具有客观的描述和代表性的流型图像。结果表明，本文提出的研究为分析和识别振荡两相流型提供了一种有效的方法。两相流相关领域的可视化实验结果将更加全面，具有客观的描述和代表性的流型图像。