Degradation modeling and remaining useful life prediction for electronic device under multiple stress influences
Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their degradation is affected by multiple types of stress, making it difficult to establish an accurate degradation model. To monitor the degradation state of ele...
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| Published in: | Scientific reports Vol. 15; no. 1; pp. 19117 - 16 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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Nature Publishing Group UK
31.05.2025
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2045-2322, 2045-2322 |
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| Abstract | Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their degradation is affected by multiple types of stress, making it difficult to establish an accurate degradation model. To monitor the degradation state of electronic devices and predict their remaining useful life at different moments, this paper obtains the degradation data of the samples by carrying out accelerated degradation experiments of power driver devices under the influence of multiple stresses, and proposes a new multi-stress-coupled accelerated degradation model based on the Wiener process. This model associates the accelerated stress with the drift coefficient of the Wiener stochastic degradation model. Finally, the MLE-SA optimization algorithm is used to obtain the unknown parameter values of the model. The method proposed in this paper incorporates accelerated stress factors into the stochastic degradation model, effectively improving the prediction accuracy and interpretability of the stochastic degradation model. To verify the accuracy of the model, the paper conducted comparative experiments on the accelerated degradation data of power driver devices and publicly available data. The results show that the multi-stress coupled accelerated degradation model based on the Wiener process proposed in this paper can well fit the accelerated degradation data of power driver devices, and the goodness-of-fit for the public dataset above 0.9, indicating that the model proposed in the paper has high accuracy. |
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| AbstractList | Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their degradation is affected by multiple types of stress, making it difficult to establish an accurate degradation model. To monitor the degradation state of electronic devices and predict their remaining useful life at different moments, this paper obtains the degradation data of the samples by carrying out accelerated degradation experiments of power driver devices under the influence of multiple stresses, and proposes a new multi-stress-coupled accelerated degradation model based on the Wiener process. This model associates the accelerated stress with the drift coefficient of the Wiener stochastic degradation model. Finally, the MLE-SA optimization algorithm is used to obtain the unknown parameter values of the model. The method proposed in this paper incorporates accelerated stress factors into the stochastic degradation model, effectively improving the prediction accuracy and interpretability of the stochastic degradation model. To verify the accuracy of the model, the paper conducted comparative experiments on the accelerated degradation data of power driver devices and publicly available data. The results show that the multi-stress coupled accelerated degradation model based on the Wiener process proposed in this paper can well fit the accelerated degradation data of power driver devices, and the goodness-of-fit for the public dataset above 0.9, indicating that the model proposed in the paper has high accuracy.Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their degradation is affected by multiple types of stress, making it difficult to establish an accurate degradation model. To monitor the degradation state of electronic devices and predict their remaining useful life at different moments, this paper obtains the degradation data of the samples by carrying out accelerated degradation experiments of power driver devices under the influence of multiple stresses, and proposes a new multi-stress-coupled accelerated degradation model based on the Wiener process. This model associates the accelerated stress with the drift coefficient of the Wiener stochastic degradation model. Finally, the MLE-SA optimization algorithm is used to obtain the unknown parameter values of the model. The method proposed in this paper incorporates accelerated stress factors into the stochastic degradation model, effectively improving the prediction accuracy and interpretability of the stochastic degradation model. To verify the accuracy of the model, the paper conducted comparative experiments on the accelerated degradation data of power driver devices and publicly available data. The results show that the multi-stress coupled accelerated degradation model based on the Wiener process proposed in this paper can well fit the accelerated degradation data of power driver devices, and the goodness-of-fit for the public dataset above 0.9, indicating that the model proposed in the paper has high accuracy. Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their degradation is affected by multiple types of stress, making it difficult to establish an accurate degradation model. To monitor the degradation state of electronic devices and predict their remaining useful life at different moments, this paper obtains the degradation data of the samples by carrying out accelerated degradation experiments of power driver devices under the influence of multiple stresses, and proposes a new multi-stress-coupled accelerated degradation model based on the Wiener process. This model associates the accelerated stress with the drift coefficient of the Wiener stochastic degradation model. Finally, the MLE-SA optimization algorithm is used to obtain the unknown parameter values of the model. The method proposed in this paper incorporates accelerated stress factors into the stochastic degradation model, effectively improving the prediction accuracy and interpretability of the stochastic degradation model. To verify the accuracy of the model, the paper conducted comparative experiments on the accelerated degradation data of power driver devices and publicly available data. The results show that the multi-stress coupled accelerated degradation model based on the Wiener process proposed in this paper can well fit the accelerated degradation data of power driver devices, and the goodness-of-fit for the public dataset above 0.9, indicating that the model proposed in the paper has high accuracy. Abstract Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their degradation is affected by multiple types of stress, making it difficult to establish an accurate degradation model. To monitor the degradation state of electronic devices and predict their remaining useful life at different moments, this paper obtains the degradation data of the samples by carrying out accelerated degradation experiments of power driver devices under the influence of multiple stresses, and proposes a new multi-stress-coupled accelerated degradation model based on the Wiener process. This model associates the accelerated stress with the drift coefficient of the Wiener stochastic degradation model. Finally, the MLE-SA optimization algorithm is used to obtain the unknown parameter values of the model. The method proposed in this paper incorporates accelerated stress factors into the stochastic degradation model, effectively improving the prediction accuracy and interpretability of the stochastic degradation model. To verify the accuracy of the model, the paper conducted comparative experiments on the accelerated degradation data of power driver devices and publicly available data. The results show that the multi-stress coupled accelerated degradation model based on the Wiener process proposed in this paper can well fit the accelerated degradation data of power driver devices, and the goodness-of-fit for the public dataset above 0.9, indicating that the model proposed in the paper has high accuracy. |
| ArticleNumber | 19117 |
| Author | Zhu, Haizhen Wen, Bincheng Li, Changjun Cheng, Jinjun Kang, Weijie Zhao, Xin |
| Author_xml | – sequence: 1 givenname: Changjun surname: Li fullname: Li, Changjun email: 1913898577@qq.com organization: Graduate School, Air Force Engineering University – sequence: 2 givenname: Jinjun surname: Cheng fullname: Cheng, Jinjun organization: Aviation Engineering School, Air Force Engineering University – sequence: 3 givenname: Haizhen surname: Zhu fullname: Zhu, Haizhen organization: Aviation Engineering School, Air Force Engineering University – sequence: 4 givenname: Bincheng surname: Wen fullname: Wen, Bincheng organization: Graduate School, Air Force Engineering University – sequence: 5 givenname: Xin surname: Zhao fullname: Zhao, Xin organization: Aviation Engineering School, Air Force Engineering University – sequence: 6 givenname: Weijie surname: Kang fullname: Kang, Weijie organization: Rocket Force University of Engineering |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40450133$$D View this record in MEDLINE/PubMed |
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| Keywords | Accelerated degradation Wiener process Multi-stress coupling Remaining useful life |
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| Snippet | Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their degradation is... Abstract Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their... |
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| SubjectTerms | 639/166/987 639/705/1041 639/705/531 Accelerated degradation Accuracy Degradation Electronic equipment Humanities and Social Sciences Multi-stress coupling multidisciplinary Remaining useful life Science Science (multidisciplinary) Useful life Wiener process |
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| Title | Degradation modeling and remaining useful life prediction for electronic device under multiple stress influences |
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