张涛,邵毅,刘乐源,郝欣,胡绍宇

• 1:辽宁东科电力有限公司
• 2:东北大学信息科学与工程学院

摘要(Abstract)：

针对燃煤电厂磨煤机制粉系统故障诊断中因数据分布不均衡导致的少数类故障诊断精度低、可解释性差的问题，提出一种融合SMOTE数据增强、Dirichlet先验平滑与贝叶斯网络的故障诊断方法。通过SMOTE技术对少数类故障样本进行特征空间扩展，缓解数据稀缺性；结合Dirichlet先验平滑优化贝叶斯网络条件概率估计，解决样本缺乏导致的零概率问题；构建分层贝叶斯网络架构，融合领域知识与数据驱动结构学习，实现故障节点快速推断与属性节点间接推断的双模式诊断策略。实验基于真实工业数据，在非均衡数据场景下，所提方法具有较高的诊断精度与可解释性，为磨煤机故障诊断提供兼具实时性、准确性及透明性的解决方案。

关键词(KeyWords)： 贝叶斯网络;故障诊断;数据不平衡;磨煤机

Abstract:

Keywords:

基金项目(Foundation): 辽宁省“揭榜挂帅”项目（2023JH1/10400050）~~

作者(Author): 张涛,邵毅,刘乐源,郝欣,胡绍宇

DOI: 10.19666/j.rlfd.202503025

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