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Degradation assessment of an IGBT with recurrence analysis and Kalman filter based data fusion

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  • Bayram Kara, Duygu

Abstract

Degradation is a nonstationary process that necessitates using a specialized measurement tool. In light of this, a degradation assessment tool has been presented in this study through the use of recurrence analysis. A fused signal has been constructed through the linear Kalman Filter Fusion Application (KFFA) to assess the growing degradation within the system. This approach aims to combine the features provided by different mediums of the system. A case study is presented using the collector-emitter current and package temperature signals collected during an IGBT's accelerated aging experiment. Time-frequency and recurrence analyses of fused and collected signals are evaluated to interpret the degradation through the nonstationary characteristics of the signals. The study has two main purposes: to investigate the combination capability of KFFA deeply for nonstationary processes and to define recurrence analysis as a degradation assessment tool.

Suggested Citation

  • Bayram Kara, Duygu, 2024. "Degradation assessment of an IGBT with recurrence analysis and Kalman filter based data fusion," Chaos, Solitons & Fractals, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:chsofr:v:186:y:2024:i:c:s0960077924007768
    DOI: 10.1016/j.chaos.2024.115224
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    References listed on IDEAS

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    1. Shao, Dongrui & Chu, Junyu & Chen, Luonan & Ma, Huanfei, 2023. "Data assimilation with hybrid modeling," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. Patel, Ashish Singh & Tiwari, Vivek & Ojha, Muneendra & Vyas, O.P., 2023. "Ontology-based detection and identification of complex event of illegal parking using SPARQL and description logic queries," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    3. Chen, Yun & Yang, Hui, 2012. "Multiscale recurrence analysis of long-term nonlinear and nonstationary time series," Chaos, Solitons & Fractals, Elsevier, vol. 45(7), pages 978-987.
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