Personal Profile

苗梦奇，2026年6月毕业于同济大学机械工程与机器人学院工业工程专业，获工学博士学位。

主要研究方向为旋转机械故障诊断与预测性维护、电池健康管理、深度学习算法设计等。

发表论文

[1] M. Miao, J. Yu and Z. Zhao, “A sparse domain adaption network for remaining useful life prediction of rolling bearings under different working conditions,” Reliability Engineering & System Safety, vol. 219, 108259, 2022. 

[2] M. Miao, Y. Sun and J. Yu, “Sparse Representation Convolutional Autoencoder for Feature Learning of Vibration Signals and its Applications in Machinery Fault Diagnosis,” IEEE Transactions on Industrial Electronics, vol. 69, no. 12, pp. 13565-13575, 2022. 

[3] M. Miao and J. Yu, “Sparse Representation Network-Based Feature Learning of Vibration Signal for Machinery Fault Diagnosis,” IEEE Transactions on Industrial Informatics, vol. 19, no. 5, pp. 6706-6716, 2023. 

[4] M. Miao and J. Yu, “Deep Feature Interactive Network for Machinery Fault Diagnosis Using Multi-source Heterogeneous Data,” Reliability Engineering & System Safety, vol. 242, 109795, 2024. 

[5] M. Miao, P. Yang, S. Yue, et al., “Multi-source self-supervised domain adaptation network for VRLA battery anomaly detection of data center under non-ideal conditions,” Energy, vol. 299, 131392, 2024.