姓名：柏林

出生年月：1972-11-06

学历学位：博士

专业技术职务：副教授

邮箱：bolin0001@aliyun.com

联系电话：13628449434

承担国家自然科学基金、国家“863”计划、“国家科技部重点研发计划”、横向科研等项目30多项。发表SCI/EI检索论文100余篇，获权发明专利3项，科学出版社出版专著1部。研究成果获国家科技进步奖二等奖1项，教育部高校发明奖1等奖1项，教育部提名国家科技进步奖1等奖1项，重庆市科技进步奖1等奖1项，教育部提名国家科技进步奖2等奖1项。

致力于高端机电装备故障诊断及寿命评估研究，在大数据运维、故障预测方面具有丰富的经验。现任中国振动工程学会动态测试专委会理事，全国高校机械测试理事专委会理事，“振动、测试与诊断”杂志编委。 

已在国内外重要学术期刊或国际重要学术会议上发表论文30余篇，其中被SCI、EI、ISTP索引20余篇。已发表的10篇代表性论文如下：

（1）Lin Bo, Chang Peng     .Fault diagnosis of rolling element bearing using more robust spectral     kurtosis and intrinsic time-scale decomposition. Journal of vibration and control.2016,Vol.12(22):1-17

（2）Lin Bo, Chang Peng, Xiaofeng     Liu, A novel redundant haar lifting wavelet analysis based fault detection     and location technique for telephone transmission lines, Measurement, 2014,     51(1)：42-52

（3）Lin Bo, Xiaofeng     Liu, Xingxi He, Measurement system for wind turbines noises assessment     based on LabVIEW, Measurement, 2011, 44(2)：445-453

（4）Chang Peng, Lin Bo*,     Vibration Signal Analysis of Journal Bearing. Supported Rotor System by     Cyclostationarity, Shock and Vibration, 2014, (2)：ID952958

（5）Liu Xiaofeng,Bo     Lin,Luo Honglin. Dynamical measurement system for wind turbine fatigue     load. Renewable Energy. 2016,86：909-921

（6）Liu Xiaofeng,Bo     Lin,L Honglin. Bearing faults diagnostics based on hybrid LS-SVM and EMD     method. Measurement,2015,59:145-166

（7）Liu Xiaofeng, Bo     Lin. Identification of resonance states of rotor-bearing system using RQA     and optimal binary tree SVM，Neurocomputing,2015,152:36-44.(SCI index)

（8）Liu Xiaofeng, Bo     Lin, Luo Hongling. Compensation method of propagating distance for guided     wave，IET     Science, Measurement and Technology,2015,9(1):9-15.

（9）Xiaofeng Liu, Lin Bo     and Chang Peng. Application of order cyclostationary demodulation to damage     detection in a direct-driven wind turbine bearing，Meas. Sci. Technol. 25, (025004),     2014. 

（10）Liu Xiaofeng,     Bo  Lin, Wang Li. Measurement and analysis of wind turbine blade     mechanical load，Journal     of Renewable Sustainable Energy,2015, 7(1):14-25.

• 机电装备故障预测及健康管理（PHM）。