柏林Lin Bai

电子邮箱:

所在单位:机械与运载工程学院

个人简介

姓名:柏林

出生年月:1972-11-06

学历学位:博士

专业技术职务: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.


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