In the evolving landscape of digital technology, the concept of digital twinning has emerged as one of the most important innovations. Digital twinning, characterized by a one‐to‐one correlation with physical structures in a digital environment, has become an important tool in transferring physical dynamics into digital replicas. This platform, integrating advanced sensor technologies and analytical tools, enables a comprehensive monitoring, diagnosis, and optimization concept. The present research focuses on the application of digital twinning in addressing the complex challenge of managing fault types in freight car brakes. A Digital Twin (DT) model of a freight car braking system is developed that forms the basis for an innovative approach to fault classification. This approach leverages the ability of the DT to emulate and analyze the behavior of the braking system under different conditions. The effectiveness of the proposed method is evaluated through extensive testing and analysis with an experimental data set. The results show that the method is able to accurately diagnose different types of faults. This represents a significant advance in the field of freight car brake system diagnosis.

中文翻译：

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开发用于故障诊断的货车制动系统操作数字孪生

在不断发展的数字技术领域，数字孪生概念已成为最重要的创新之一。数字孪生的特点是与数字环境中的物理结构一对一相关，已成为将物理动态转换为数字复制品的重要工具。该平台集成了先进的传感器技术和分析工具，实现了全面的监控、诊断和优化概念。目前的研究重点是数字孪生在解决管理货车制动器故障类型的复杂挑战方面的应用。开发了货车制动系统的数字孪生 (DT) 模型，为故障分类的创新方法奠定了基础。这种方法利用了 DT 的能力来仿真和分析制动系统在不同条件下的行为。通过对实验数据集进行广泛的测试和分析来评估所提出方法的有效性。结果表明，该方法能够准确诊断不同类型的故障。这代表了货车制动系统诊断领域的重大进步。