Tianyang Wang

Assistant Professor

Address: Lee Shau Kee Science and Technique Building A1012

Tel: 62790532

Fax: 62790532

E-mail: wty19850925@126.com wty19850925@tsinghua.edu.cn

属性1 Assistant Professor 属性2 Address: Lee Shau Kee Science and Technique Building A1012
属性3 Tel: 62790532 属性4 Fax: 62790532
属性5 E-mail: wty19850925@126.com wty19850925@tsinghua.edu.cn 属性6
Education background

2008/09-2015/01, Beijing Jiaotong University, Doctor's degree

2004/09-2008/06, Beijing Jiaotong University, Bachelor's degree

Experience

2018/03-present, Department of Mechanical Engineer, Tsinghua University, Assistant Professor

2015/03-2018/03, Department of Mechanical Engineer, Tsinghua University, Post-doctor

Areas of Research Interests/ Research Projects

Mainly engaged in research work in the field of fault diagnosis and signal analysis of large rotating machinery such as wind turbines and aero engines.

Research directions: Modern signal processing, Dynamic modeling, Artificial intelligence, Pattern recognition.

Papers and Patents

[1]Kong Y, Wang T, Chu F. Meshing frequency modulation assisted empirical wavelet transform for fault diagnosis of wind turbine planetary ring gear[J]. Renewable Energy, 2019, 132: 1373-1388.

[2]Zhao D, Wang T, Chu F. Deep convolutional neural network based planet bearing fault classification[J]. Computers in Industry, 2019, 107: 59-66.

[3]Wang T, Han Q, Chu F, et al. Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review[J]. Mechanical Systems and Signal Processing, 2019, 126: 662-685.

[4]Wang T, Chu F, Feng Z. Meshing frequency modulation (MFM) index-based kurtogram for planet bearing fault detection[J]. Journal of Sound and Vibration, 2018, 432: 437-453.

[5]Yun K, WANG T, CHU F. Adaptive TQWT filter based feature extraction method and its application to detection of repetitive transients[J]. SCIENCE CHINA Technological Sciences.

[6]Wang T, Chu F, Han Q. Fault diagnosis for wind turbine planetary ring gear via a meshing resonance based filtering algorithm[J]. ISA transactions, 2017, 67: 173-182.

[7]Wang T, Chu F, Han Q, et al. Compound faults detection in gearbox via meshing resonance and spectral kurtosis methods[J]. Journal of Sound and Vibration, 2017, 392: 367-381.

[8]Feng Z, Chen X, Wang T. Time-varying demodulation analysis for rolling bearing fault diagnosis under variable speed conditions[J]. Journal of Sound and Vibration, 2017, 400: 71-85.

[9]Kong Y, Wang T, Li Z, et al. Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet energy spectrum[J]. Frontiers of Mechanical Engineering, 2017, 12(3): 406-419.

[10] Wang T, Han Q, Chu F, et al. A new SKRgram based demodulation technique for planet bearing fault detection[J]. Journal of Sound and Vibration, 2016, 385: 330-349.

[11] Li C, Liang M, Wang T. Criterion fusion for spectral segmentation and its application to optimal demodulation of bearing vibration signals[J]. Mechanical Systems and Signal Processing, 2015, 64: 132-148.

[12]Wang T, Liang M, Li J, et al. Bearing fault diagnosis under unknown variable speed via gear noise cancellation and rotational order sideband identification[J]. Mechanical Systems and Signal Processing, 2015, 62: 30-53.

[13]Wang T, Liang M, Li J, et al. Rolling element bearing fault diagnosis via fault characteristic order (FCO) analysis[J]. Mechanical Systems and Signal Processing, 2014, 45(1): 139-153.

[14] Cheng W, Gao R X, Wang J, et al. Envelope deformation in computed order tracking and error in order analysis[J]. Mechanical Systems and Signal Processing, 2014, 48(1-2): 92-102.

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