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首页> 外文期刊>IEEE Transactions on Industrial Electronics >Multiple-Model-Based Diagnosis of Multiple Faults With High-Speed Train Applications Using Second-Level Adaptation
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Multiple-Model-Based Diagnosis of Multiple Faults With High-Speed Train Applications Using Second-Level Adaptation

机译：二级适应高速列车应用的多模型基础诊断

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摘要

Due to the time-varying characteristics and the interacted nature of multiple faults in the high-speed train (HST), the fault modeling, isolation, and severity estimation cannot be described accurately using a single model, which may result in poor performance of the conventional fault diagnosis methods. This article introduces the idea of multiple models and second-level adaptation techniques to diagnose multiple faults of the HST traction motor. First, a reduced model description for the multiple faults is given. Then, a multiple fault isolation framework is developed to simplify the time-varying fault parameters space segmentation. Based on the decoupled fault set, a fault estimation scheme with second-level adaptation is used to provide a reliable alarm priority for different fault scenarios. A case study is performed to verify the effectiveness of the proposed approach.
机译：由于高速列车（HST）中的多个故障的时变特性和互动性，使用单个型号不能准确描述故障建模，隔离和严重性估计，这可能导致性能差传统故障诊断方法。本文介绍了多种模型和二级适配技术的思想，以诊断HST牵引电机的多个故障。首先，给出了对多个故障的降低的模型描述。然后，开发了多个故障隔离框架以简化时变故障参数空间分割。基于解耦故障集，使用具有第二级适应的故障估计方案来提供不同故障场景的可靠警报优先级。进行案例研究以验证所提出的方法的有效性。

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