Ageing defect detection on IGBT power modules by artificial training methods based on pattern recognition
Ageing defect detection on IGBT power modules by artificial training methods based on pattern recognition
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DOI：
10.1016/j.microrel.2010.08.006
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发表时间：
2011-02-01
影响因子：
1.6
通讯作者：
Boudart, B.
中科院分区：
文献类型：
--
作者：
Oukaour, A.;Tala-Ighil, B.;Boudart, B.
功率绝缘栅双极晶体管（IGBT）模块的老化主要与应用于器件的热和热机械约束有关。这种老化会导致器件性能退化和外观缺陷，从而导致故障。为了避免这些故障，跟踪设备运行和检测老化状态仍然是一个优先事项。本文首先介绍了1200 V-30 A IGBT模块在功率循环下的老化试验，目的是突出在线和实时可测量的老化外部指标。其次，这些指标被用来开发一个故障诊断方法。诊断是通过基于模式识别的人工训练方法来实现的。(C)2010爱思唯尔有限公司版权所有。
The ageing of power insulated gate bipolar transistor (IGBT) modules is mainly related to thermal and thermomechanical constraints applied to the device. This ageing causes degradation of the device performances and defects appearance which can lead to failures. To avoid these failures, the follow-up of the device operation and the detection of an ageing state remain a priority. This paper presents, at first, ageing tests of 1200 V-30 A IGBT module subjected to power cycling with the aim to highlight online and real-time measurable external indicators of ageing. Secondly, these indicators are used to develop a failure diagnosis method. The diagnosis is realized by artificial training methods based on pattern recognition. (C) 2010 Elsevier Ltd. All rights reserved.