科研工作与成果

1. 参与科研项目

[1] 多元序列全时间尺度分解方法及其在面齿轮分扭传动装置故障诊断中的应用，国家自然科学基金面上项目，2023-2026，参与；

[2] 可伸缩移位超圆盘张量机及其在复杂机电系统故障诊断和寿命预测中的应用，国家自然科学基金面上项目，2020-2023，参与。

2. 科研成果

[1] Wu H, Kundu P. Review of physics augmented: Physics-guided, physics-informed, and physics-encoded machine learning models in condition monitoring. Engineering Applications of Artificial Intelligence, 2026, 182: 116100.

[2] Wu H, Cheng J, Kundu P. Modulated model network: A physics-informed machine learning method for high-precision signal reconstruction and enhanced fault diagnostics. Engineering Applications of Artificial Intelligence, 2026, 165: 113514.

[3] Wu H, Cheng J, Hu N, Cheng Z, Yang Y. Quaternion empirical Ramanujan Fourier decomposition and its application in gear fault diagnosis. Structural Health Monitoring, 2024, 23(5): 2713-2736.

[4] Wu H, Cheng J, Nie Y, Wang J, Yang Y. Multivariate complex modulation model decomposition and its application to gear fault diagnosis. Digital Signal Processing, 2023, 135: 103940.

[5] Zheng X, Wu H, Jin D, Cheng J, Yang Y. Geometric Algebra Symplectic Singular Decomposition: A Novel Multivariate Signal Decomposition Method for Gear Fault Diagnosis. Digital Signal Processing, 2026: 106002.

[6] Liu F, Cheng Z, Wu H, Cheng J. A novel variable multilevel random feature decomposition method for gear fault diagnosis. Structural Health Monitoring, 2025: 14759217251360635.

[7] Duan G, Zheng S, Cheng Z, Wu H, Xia B. Gear Fault Detection via Deep‐Subwavelength Rainbow Trapping Effect of Higher‐Order Topological Mechanical Metamaterials. Advanced Functional Materials. 2025, 35(31): 2425815.

社会学术团体兼职

主要研究方向

设备状态监测与智能运维，旋转机械信号处理，深度学习。

近3年指导研究生的就业情况