趙明航

2009.09-2013.06 重慶大學 機械設計製造及其自動化 本科

2013.09-2018.12 重慶大學 機械工程 博士

2016.09-2017.09 美國馬里蘭大學帕克分校 訪學

[1] 國家自然科學基金青年項目：熱流固耦合作用下圖注意力驅動的船舶燃燒室部件故障預測方法研究（主持，52105545，24萬，2022.01-2024.12）

[2] 山東省自然科學基金青年項目：深度幅頻解調模式下航空發動機主軸軸承微弱故障診斷方法研究（主持，ZR2020QE156，10萬，2021.01-2023.12）

以第一/通訊作者身份發表SCI論文11篇，其中中科院大類一區Top期刊5篇，IEEE Trans 5篇，ESI高被引論文2篇。

[1] M. Zhao*, X. Fu, Y. Zhang, L. Meng, B. Tang. Highly imbalanced fault diagnosis of mechanical systems based on wavelet packet distortion and convolutional neural networks[J]. Advanced Engineering Informatics, 2022, 51: 101535. (IF=5.603)

[2] M. Zhao*, X. Fu, Y. Zhang, L. Meng, S. Zhong. Data augmentation via randomized wavelet expansion and its application in few-shot fault diagnosis of aviation hydraulic pumps[J]. IEEE Transactions on Instrumentation and Measurement, 2021, accepted. (IF=4.016)

[3] L. Meng, M. Zhao*, Z. Cui, X. Zhang, S. Zhong. Empirical mode reconstruction: Preserving intrinsic components in data augmentation for intelligent fault diagnosis of civil aviation hydraulic pumps[J]. Computers in Industry, 2022, 134: 103557. (IF=7.635)

[4] S. Fu, Y. Zhang*, L. Lin, M. Zhao*, S. Zhong. Deep residual LSTM with domain-invariance for remaining useful life prediction across domains[J]. Reliability Engineering & System Safety, 2021, 216: 108012. (中科院大類1區，Top期刊，IF=6.188)

[5] M. Zhao*, S. Zhong, X. Fu, B. Tang, S. Dong, M. Pecht. Deep residual networks with adaptively parametric rectifier linear units for fault diagnosis[J]. IEEE Transactions on Industrial Electronics, vol. 68, no. 3, pp. 2587-2597, 2021. (中科院大類1區，Top期刊，IF=8.236)

[6] M. Zhao*, S. Zhong, X. Fu, B. Tang, M. Pecht. Deep residual shrinkage networks for fault diagnosis[J]. IEEE Transactions on Industrial Informatics, vol. 16, no. 7, pp. 4681-4690, 2020. (中科院大類1區，Top期刊，IF=10.215，ESI高被引論文)

[7] M. Zhao, B. Tang*, L. Deng, M. Pecht. Multiple wavelet regularized deep residual networks for fault diagnosis[J]. Measurement, vol. 152, article no. 107331, 2020. (IF=3.927)

[8] M. Zhao, M. Kang*, B. Tang, M. Pecht. Multiple wavelet coefficients fusion in deep residual networks for fault diagnosis[J]. IEEE Transactions on Industrial Electronics, vol. 66, no. 6, pp. 4696-4706, 2019. (中科院大類1區，Top期刊，IF=8.236)

[9] M. Zhao, M. Kang*, B. Tang, M. Pecht. Deep residual networks with dynamically weighted wavelet coefficients for fault diagnosis of planetary gearboxes[J]. IEEE Transactions on Industrial Electronics, vol. 65, no. 5, pp. 4290-4300, 2018. (中科院大類1區，Top期刊，IF=8.236，ESI高被引論文)

[10] M. Zhao, B. Tang*, Q. Tan. Bearing remaining useful life estimation based on time–frequency representation and supervised dimensionality reduction[J]. Measurement, vol. 86, pp. 41-55, 2016. (IF=3.927)

[11] M. Zhao, B. Tang*, Q. Tan. Fault diagnosis of rolling element bearing based on S transform and gray level co-occurrence matrix[J]. Measurement Science and Technology, vol. 26, no. 8, art. no. 085008, 2015. (IF=2.046)

獲重慶市優秀博士學位論文、重慶大學優秀博士學位論文

機器人專業《模式識別》

機械專業《設備檢測與診斷》

機械專業《機械結構分析基礎》