Research on a Fault Diagnosis Method for the Braking Control System of an Electric Multiple Unit Based on Deep Learning Integration

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2024-01-17 DOI:10.3390/machines12010070

Yueheng Wang, Haixiang Lin, Dong Li, Jijin Bao, Nana Hu

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引用次数: 0

Abstract

A fault diagnosis method based on deep learning integration is proposed focusing on fault text data to effectively improve the efficiency of fault repair and the accuracy of fault localization in the braking control system of an electric multiple unit (EMU). First, the Borderline-SMOTE algorithm is employed to synthesize minority class samples at the boundary, addressing the data imbalance and optimizing the distribution of data within the fault text. Then, a multi-dimensional word representation is generated using the multi-layer bidirectional transformer architecture from the pre-training model, BERT. Next, BiLSTM captures bidirectional context semantics and, in combination with the attention mechanism, highlights key fault information. Finally, the LightGBM classifier is employed to reduce model complexity, enhance analysis efficiency, and increase the practicality of the method in engineering applications. An experimental analysis of fault data from the braking control system of the EMU indicates that the deep learning integration method can further improve diagnostic performance.

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基于深度学习集成的电动多联机制动控制系统故障诊断方法研究

针对故障文本数据，提出了一种基于深度学习集成的故障诊断方法，以有效提高电动多联机组（EMU）制动控制系统的故障修复效率和故障定位精度。首先，采用 Borderline-SMOTE 算法在边界合成少数类样本，解决数据不平衡问题，优化故障文本内的数据分布。然后，利用预训练模型 BERT 的多层双向变换器架构生成多维词表示。接着，BiLSTM 捕捉双向上下文语义，并与注意力机制相结合，突出关键故障信息。最后，采用 LightGBM 分类器来降低模型复杂度，提高分析效率，并增加该方法在工程应用中的实用性。对电磁单元制动控制系统故障数据的实验分析表明，深度学习集成方法可进一步提高诊断性能。

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来源期刊

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464

期刊介绍： ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.