TY - GEN
T1 - Generalization Method of Physics of Failure Model Based on Extreme Learning Machine
AU - Li, Mengying
AU - Chen, Ying
AU - Yao, Yuan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The traditional method of using theoretical deduction and experimental regression to Physics of Failure(PoF) model is only used in specific scenarios, and it is difficult to popularize and apply. Aiming at the limitations of traditional PoF modeling method, this paper proposes a generalization method of PoF model based on Extreme Learning Machine(ELM). In this paper, the corrosion PoF model of electronic device was taken as an example to demonstrate the proposed method, and the generalization ability of the corrosion PoF model is improved.
AB - The traditional method of using theoretical deduction and experimental regression to Physics of Failure(PoF) model is only used in specific scenarios, and it is difficult to popularize and apply. Aiming at the limitations of traditional PoF modeling method, this paper proposes a generalization method of PoF model based on Extreme Learning Machine(ELM). In this paper, the corrosion PoF model of electronic device was taken as an example to demonstrate the proposed method, and the generalization ability of the corrosion PoF model is improved.
KW - Extreme Learning Machine(ELM)
KW - Physics of Failure(PoF)
KW - corrosion
KW - generalization
UR - https://www.scopus.com/pages/publications/105030323368
U2 - 10.1109/ICRMS63553.2024.00020
DO - 10.1109/ICRMS63553.2024.00020
M3 - 会议稿件
AN - SCOPUS:105030323368
T3 - Proceedings - 2024 15th International Conference on Reliability, Maintenance and Safety, ICRMS 2024
SP - 72
EP - 77
BT - Proceedings - 2024 15th International Conference on Reliability, Maintenance and Safety, ICRMS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Reliability, Maintenance and Safety, ICRMS 2024
Y2 - 31 July 2024 through 2 August 2024
ER -