近几年来在国际期刊和国际会议上发表论文90余篇，其中SCI收录44篇。获美国国家发明专利授权1项并由Springer-Verlag出版公司出版专著“Wavelets: Theory and Applications for Manufacturing” 1部。负责或参与完成国家级、省部级项目多项。多次担任国际会议分会主席及国际会议程序委员会成员并应邀为多个国际期刊审稿。
SCI期刊论文
[1] R. Yan, R. Gao, and X. Chen, “Wavelets for fault diagnosis of rotary machines: a review with applications”,Signal Processing, Vol. 96, pp. 1-15, 2014.
[2] R. Yan,H. Sun, and Y. Qian, “Energy-aware sensor node design with its application in wireless sensor networks”,IEEE Transactions on Instrumentation and Measurement, Vol. 62, No.5, pp. 1183-1191, 2013.
[3] R. Yan, Y. Liu, and R. Gao, “Permutation entropy: a nonlinear statistical measure for status characterization of rotary machines”,Mechanical Systems and Signal Processing, Vol. 29, pp.474-484, May 2012.
[4] R. Yan and R. Gao, “A nonlinear noise reduction approach to vibration analysis for bearing health diagnosis”,ASME Journal of Computational and Nonlinear Dynamics,Vol. 7, No.2, pp. 021004-1-7, April, 2012.
[5] R. Yan and R. Gao, “Wavelet domain principal feature analysis for spindle health diagnosis”,Structural Health Monitoring, Vol. 10, No. 6, pp. 631-642, November 2011.
[6] R. Yan and R. Gao, “Harmonic wavelet-based data filtering for enhanced machine defect identification”,Journal of Sound and Vibration, Vol. 329, No. 15, pp. 3203-3217, July, 2010.
[7] R. Yan and R. Gao, “Energy-based feature extraction for defect diagnosis in rotary machines”,IEEE Transactions on Instrumentation and Measurement, Vol. 58, No. 9, pp.3130-3139, September, 2009.
[8] R. Yan, R. Gao, and C. Wang, “Experimental evaluation of a unified time-scale-frequency technique for bearing defect feature extraction”,ASME Journal of Vibration and Acoustics,Vol. 131, No. 4, pp.041012, August, 2009.
[9] R. Yanand R. Gao, “Base wavelet selection for bearing vibration signal analysis”,International Journal of Wavelets, Multi-resolution, and Information Processing, Vol. 7, No. 4, pp.411-426, July, 2009.
[10]R. Yan and R. Gao, “Multi-scale enveloping spectrogram for vibration analysis in bearing defect diagnosis”,Tribology International, Vol. 42, No. 2, pp. 293-302,February 2009.
其他在研项目
[1] 基于小波理论和多时间尺度建模的旋转部件健康监测研究
[2] 航空发动机主轴承故障分析研究
[3] 基于混合模型的旋转部件寿命预测研究
