2012.03-2015.06 上海交通大学机械工程系 博士
2009.09-2012.03 上海交通大学机械工程系 硕士
2005.09-2009.06 华侨大学机械工程系 学士

2019.02-至今 上海交通大学
2015.05-2019.01 上海交通大学 博士后
2016.09-2018.09 The University of Iowa 博士后

系统辨识(动力学反问题)
信号处理
机器学习
深度学习
机械振动

招收对人工智能和数据科学感兴趣的硕、博士研究生
招收系统辨识和机器学习方向的博士后
欢迎联系！

Reviewer of Automatica、 IEEE Transactions on Automatic Control and IEEE Transactions on Signal Processing et al.

国家自然科学基金优秀青年基金 2025-2027 复杂高维非线性系统辨识
国家重点研发计划课题(主持) 2021-2024 基于大样本的轴承信号分解、故障诊断及寿命预测研究
国家自然科学基金面上项目2024-2027(主持) 基于动态数据和物理模型双驱动的复杂非线性系统辨识方法研究
国家自然科学基金面上项目2021-2024(主持) 高维非线性系统变量选择及辨识方法研究
国家自然科学基金青年项目2018-2020((主持)
上海市浦江人才支持计划(A类)(主持)
上海市自然科学基金(主持)
博士后特别资助(主持)
博士后面上项目(主持)
国家重点实验室重点项目(主持)

Cheng C , Shan D , Teng Y , Zhao B , Peng Z , He Q, Semi-supervised fault diagnosis for gearboxes: a novel method based on a hybrid classification network and weighted pseudo-labeling, IEEE Sensors Journal, 2023, 23(14): 16373-16383.
Zhao B, Cheng C*, Zhao S, Peng Z, Hybrid semi-supervised learning for rotating machinery fault diagnosis based on grouped pseudo-labeling and consistency regularization, IEEE Transactions on Instrumentation and Measurement, 2023, 72, 3515812.
Li X , Cheng C* , Peng Z, An unsupervised condition monitoring method for rolling bearings based on compound feature selection and multi-step-aware BiGRU-VAE, IEEE Transactions on Instrumentation and Measurement, 2023.
Zhao S, Cheng C*, Lin M, Peng Z, Meng G, A nonlinearity-sensitive approach for early damages detection using NOFRFs and the Hybrid-LSTM Model, IEEE Transactions on Instrumentation and Measurement, 2023.
Shan D, Cheng C*, Li L, Peng Z, He Q. Semi-supervised fault diagnosis of gearbox using weighted graph-based label propagation and virtual adversarial training. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 3503411.
Cheng C. , Bai E. , Peng Z. , Identification of sparse Volterra systems, IEEE Transactions on Automatic Control, 2022, 67(4): 2027–2032.
Cheng C, Zhao, B., Fu, C. Peng Z. Meng G., A two-stage sparse algorithm for localization and characterization of local nonlinear structures, Journal of Sound and Vibration, 2022, 116823.
Lin M, Cheng C*, Zhang G Z, Zhao B, Peng Z, Meng G. Identification of Bouc-Wen hysteretic systems based on a joint optimization approach. Mechanical Systems and Signal Processing, 2022, 180: 109404.
Lin M, Sun B, Cheng C*, Zhao B, Peng Z, Meng G. Alternating state-parameter identification of Bouc-Wen hysteretic systems from steady-state harmonic response. Journal of Sound and Vibration, 2022, 538: 117242.
Lu J, Cheng C*, Zhao B, Peng Z. Relation-aware attentive neural processes model for remaining useful life prediction. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 3522809.
Zhao B, Cheng C*, Zhang G, Lin M, Peng Z, Meng G. An Instance and Feature-Based Hybrid Transfer Model for Fault Diagnosis of Rotating Machinery With Different Speeds. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 3525612.
Mu B., Chen T., Cheng C., Bai E., Persistence of excitation for identifying switched linear systems, Automatica, 2022, 137, 110142.
Cheng C. , Bai E., Peng Z., Variable Selection According to Goodness of Fit in Nonparametric Nonlinear System Identification, IEEE Transactions on Automatic Control, 2021, 66(7): 3184-3196.
Cheng, C., Bai, E. Variable selection based on squared derivative averages, Automatica, 2021, 127, 109491.
Lin M., Cheng C.*, Peng Z., Dong X., Qu Y., Meng G., Nonlinear dynamical system identification using the sparse regression and separable least squares methods, Journal of Sound and Vibration, 2021, 505, 116141.
Zhao B., Cheng C.*, Peng Z., He Q., Meng G., Hybrid pre-training strategy for deep denoising neural networks and its application in machine fault diagnosis, IEEE Transactions on Instrumentation and Measurement, 2021, 70.
Zhao B., Cheng C.*, Tu G., Peng Z., He Q., Meng G. An interpretable denoising layer for neural networks based on reproducing kernel Hilbert space and its application in machine fault diagnosis, Chinese Journal of Mechanical Engineering (English Edition), 2021, 34(1), 44.
Wu X., Zhang Y., Cheng C., Peng Z., A hybrid classification autoencoder for semi-supervised fault diagnosis in rotating machinery, Mechanical Systems and Signal Processing, 2021, 149, 107327.
Zhao B., Cheng C.*, Peng Z., Dong X., Meng G., Detecting the early damages in structures with nonlinear output frequency response functions and the CNN-LSTM model, IEEE Transactions on Instrumentation and Measurement, 2020, 69(12): 9557-9567.
Wu X., Peng Z., Ren J., Cheng C., Zhang W., Wang D., Rub-impact fault diagnosis of rotating machinery based on 1-D convolutional neural networks, IEEE Sensors Journal, 2020, 20(15), 8349-8363.
Wang Y., Cheng C., Volterra series identification and its applications in structural identification of nonlinear block-oriented systems, International Journal of Systems Science, 2020, 1959-1968.
[1] C. Cheng, E. Bai, Z. Peng, Consistent Variable Selection for a High-Dimensional Nonparametric Nonlinear System by Inverse and Contour Regression, IEEE Transactions on Automatic Control, 2019, 64: 2653-2664.
[2] C. Cheng, E. Bai, Z. Peng, Testing If A Nonlinear System Is Additive Or Not, Automatica, 2019, 104: 134-140.
[3] C. Cheng, E. Bai, Z. Peng, Ranking the Importance of Variables in Nonlinear System Identification, Automatica, 2019, 103: 472-479.
[4] C. Cheng, X. Dong, Z. Peng, W. Zhang, G. Meng, Kautz basis expansion-based Hammerstein system identification through separable least squares method, Mechanical Systems and Signal Processing, 2019, 121: 929-941.
[5] E. Bai, C. Cheng, W. Zhao, Variable Selection of High-Dimensional Non-Parametric Nonlinear Systems by Derivative Averaging to Avoid the Curse of Dimensionality, Automatica, 2019, 101: 138-149.
[6] C. Cheng, E. Bai, Ranking Variables in Nonlinear Nonparametric Additive System Identification, IFAC-PapersOnLine, 2018, 51(15), 1-6.
[7] C. Cheng, Z. Peng, X. Dong, W. Zhang, G. Meng, Impulse response function identification of linear mechanical systems based on Kautz basis expansion with multiple poles. International Journal of Systems Science, 2018, 49 (7) 1559-1571.
[8] E. Bai, C. Cheng, A Data-Driven Basis Function Approach in Non-Parametric Nonlinear System Identification, Uncertainty in Complex Networked Systems, 2018, 1-47.
[9] C. Cheng, Z. Peng, X. Dong, W. Zhang, G. Meng, Nonlinear System Identification Using Kautz Basis Expansion-based Volterra-PARAFAC model, Nonlinear dynamics, 2018, 94(3), 2277–2287.
[10] C. Cheng, Z. Peng, W. Zhang, G. Meng, Volterra-series-based nonlinear system modeling and its engineering applications: A state-of-the-art review. Mechanical Systems and Signal Processing, 2017, 87: 340-364.
[11] C. Cheng, Z. Peng, X. Dong, W. Zhang, G. Meng, A novel approach for identification of cascade of Hammerstein model. Nonlinear Dynamics, 2016, 86(1): 513-522.
[12] Y. Deng , C. Cheng, Y Yang, Z. Peng. Parametric Identification of Nonlinear Vibration Systems Via Polynomial Chirplet Transform. Journal of Vibration and Acoustics, 2016, 138(5): 051014.
[13] C. Cheng, Z. Peng, X. Dong, W. Zhang, G. Meng, A novel damage detection approach by using Volterra kernel functions based analysis. Journal of the Franklin Institute, 2015, 352(8): 3098-3112.
[14] C. Cheng, Z. Peng, X. Dong, W. Zhang, G. Meng, Analysis of locally nonlinear two dimensional periodic structures using NOFRFs. Vibration Engineering and Technology of Machinery, 2015, 23: 811-823.
[15] C. Cheng, Z. Peng, W. Zhang, G. Meng, Wavelet basis expansion-based Volterra kernel function identification through multilevel excitations. Nonlinear Dynamics, 2014, 76(2): 985-999.
[16] C. Cheng, Z. Peng, X. Dong, W. Zhang, G. Meng, Locating nonlinear components in two dimensional periodic structures based on NOFRFs. International Journal of Nonlinear Mechanics, 2014, 67:198-208.
[17] C. Cheng, Z. Peng, W. Zhang, G. Meng, Wavelet basis expansion-based spatio-temporal Volterra kernels identification for nonlinear distributed parameter systems. Nonlinear Dynamics, 2014, 78(2): 1179-1192.
[18] 彭志科, 程长明. Volterra级数理论研究进展与展望. 科学通报, 2015, 60: 1874-1888.
[19] 程长明, 彭志科, 孟光. 一类非线性系统的随机振动频率响应分析研究. 力学学报, 2011, 43(5): 905-913.