基于MultiScaleFormer网络的IGBT门氧化物层性能降解的预测
Shilie He1,2,3, Meiling Yu4, Yiqiang Chen2,3
1School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China.
Micromachines
|August 29, 2024
概括
使用门泄漏电流监测绝缘门双极晶体管 (IGBT) 门氧化物降解是可行的. 新的MultiScaleFormer模型准确地预测IGBT性能下降,优于其他低MAE0.0087.7的方法.
科学领域:
- 电力电子 电力电子 电力电子
- 可靠性工程可靠性工程
- 机器学习 机器学习
背景情况:
- 绝缘门双极晶体管 (IGBT) 在功率电子中至关重要,而门氧化物降解是关键的故障模式.
- 有效的健康管理需要准确预测IGBT性能退化.
研究的目的:
- 为了确定IGBT门氧化物降解的可靠前体.
- 开发和验证IGBT的先进降解预测模型.
主要方法:
- 门泄漏电流被选为故障前体参数.
- 使用特征选择和融合技术 (时间域分析,灰度相关性,马哈拉诺比斯距离,卡尔曼波器).
- 开发了一种改进的降解预测模型,MultiScaleFormer,灵感来自iTransformer.
主要成果:
- 一个健康指标成功地提取出来,以表征IGBT门氧化物衰老.
- 与LSTM,CNN,SVR,GPR,CNN-LSTM和变压器模型相比,MultiScaleFormer显示出更高的适配精度.
- 通过MultiScaleFormer模型,平均绝对误差 (MAE) 降至0.0087.
结论:
- 门泄漏电流是IGBT门氧化物故障的可行故障前体.
- 多尺度形式模型为预测IGBT性能下降提供了一种可行且准确的方法.
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