李继猛 - 燕山大学 - 电气工程学院

个人简介

研究领域

机械系统动态信号分析；随机共振理论研究及应用；大型装备运行状态监测与智能诊断

专利一种滚动轴承故障诊断方法及系统基于平均随机弱正交匹配追踪的滚动轴承故障稀疏诊断方法一种基于滑动窗的随机共振微弱冲击特征增强提取方法科研项目面向大数据智能运维的风电机组故障诊断与预警关键技术研究, 2019-07-01, 进行大数据驱动的风电机组健康监测与预警关键技术研究, 2018-01-01, 进行风电传动系统多模态监测信息学习融合及健康预警诊断, 2018-08-20, 进行多激励耦合下行星齿轮传动系统故障演化机理及随机共振诊断方法研究, 2017-01-01, 进行变工况下风电机组健康预警与定量诊断, 2016-11-15, 进行行星齿轮传动系统机电耦合动态特性与微弱故障诊断研究, 2015-08-18, 进行噪声驱动下风电装备传动系统微弱故障诊断方法研究, 2015-06-30-2016-08-31, 完成风电装备传动系统早期微弱故障增强提取与诊断方法研究, 2015-06-09, 进行基于噪声利用机制的微弱信号特征提取方法研究, 2014-09-12-2019-01-07, 完成

近期论文

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Jimeng Li, Xifeng Yao, Xiangdong Wang, Qingwen Yu, Yungang Zhang. Multiscale local features learning based on BP neural network for rolling bearing intelligent fault diagnosis[J]. Measurement, 2020, https://doi.org/10.1016/j.measurement.2019.107419. (SCI，IF 2.791) Jimeng Li, Hui Wang, Xiangdong Wang, Yungang Zhang. Rolling bearing fault diagnosis based on improved adaptive parameterless empirical wavelet transform and sparse denoising[J]. Measurement, 2020, https://doi.org/10.1016/j.measurement.2019.107392. (SCI，IF 2.791) Jimeng Li, Xifeng Yao, Hui Wang ,et al. Periodic impulses extraction based on improved adaptive VMD and sparse code shrinkage denoising and its application in rotating machinery fault diagnosis[J]. Mechanical Systems and Signal Processing, 2019, 568-589. (SCI 中科院二区 Top) Jimeng Li, Jinfeng Zhang, Ming Li, et al. A novel adaptive stochastic resonance method based on coupled bistable systems and its application in rolling bearing fault diagnosis[J]. Mechanical Systems and Signal Processing, 2019, 128-145. (SCI 中科院二区 Top) Jimeng Li, Hui Wang, Jinfeng Zhang, et al. Impact fault detection of gearbox based on variational mode decomposition and coupled underdamped stochastic resonance[J]. ISA Transactions, 2019. (SCI 中科院二区) Jimeng Li, Ming Li, Jinfeng Zhang, et al. Frequency-shift multiscale noise tuning stochastic resonance method for fault diagnosis of generator bearing in wind turbine[J]. Measurement, 2019. 421-432. (SCI，IF 2.791) Jimeng Li, Ming Li, Xifeng Yao, et al. An adaptive randomized orthogonal matching pursuit algorithm with sliding window for rolling bearing fault diagnosis[J]. IEEE Access, 2018. (SCI，中科院二区) Jimeng Li, Ming Li, Jinfeng Zhang. Rolling bearing fault diagnosis based on time-delayed feedback monostable stochastic resonance and adaptive minimum entropy deconvolution[J]. Journal of Sound and Vibration, 2017: 139-151. (SCI，IF 3.123) Jimeng Li, Yungang Zhang, Ping Xie. A new adaptive cascaded stochastic resonance method for impact features extraction in gear fault diagnosis. Measurement, 2016, 91: 499-508. (SCI，IF 2.791) Jimeng Li, Jinfeng Zhang. Adaptive multiscale noise control enhanced stochastic resonance method based on modified eemd with its application in bearing fault diagnosis. Shock and Vibration, 2016: 1485412_1:13. (SCI，IF 1.62) Jimeng Li, Xuefeng Chen, Zhengjia He. Multi-stable stochastic resonance and its application research on mechanical fault diagnosis. Journal of Sound and Vibration, 2013, 22: 5999-6015. (SCI，IF 3.123) Jimeng Li, Xuefeng Chen, Zhengjia He. Adaptive stochastic resonance method for impact signal detection based on sliding window. Mechanical Systems and Signal Processing, 2013, 36: 240-255. (SCI 中科院二区 Top) Jimeng Li, Xuefeng Chen, Zhaohui Du, et al. A New noise-controlled second-order enhanced stochastic resonance method with its application in wind turbine drivetrain fault diagnosis. Renewable Energy, 2013, 60: 7-19. (SCI 中科院二区) Guoying Li, Jimeng Li, Shibin Wang, et al. Quantitative evaluation on the performance and feature enhancement of stochastic resonance for bearing fault diagnosis. Mechanical System and Signal Processing, 2016, 2016, 81: 108-125. (SCI 中科院二区) 李继猛，李铭，王慧，等. 基于相关正交匹配追踪算法的风电机组滚动轴承稀疏故障诊断方法. 中国机械工程，2018. 李继猛，张云刚，张金凤，等. 基于自适应随机共振的齿轮微弱冲击故障增强提取方法研究. 计量学报, 2017. 李继猛，黄梦君，谢平，等. 同步压缩-交叉小波变换及滚动轴承故障特征增强. 计量学报, 2017. 李继猛，张金凤，张云刚，等. 基于自适应随机共振和稀疏编码收缩算法的齿轮故障诊断方法. 中国机械工程，2016. 论文成果 More>> 何群,王红,江国乾,谢平,李继猛,王腾超.基于相关主成分分析和极限学习机的风电机组主轴承状态监测研究.计量学报.2018 李继猛,黄梦君,谢平,江国乾,陈萌,何群.同步压缩-交叉小波变换及滚动轴承故障特征增强.计量学报.2018 李继猛,李铭,王慧,张金凤,张云刚.基于相关正交匹配追踪算法的风电机组滚动轴承稀疏故障诊断方法.中国机械工程.2018 李继猛,李铭,张金凤.Rolling bearing fault diagnosis based on time-delayed feedback monostable stochastic resonance and adaptive minimum entropy deconvolution.JOURNAL OF SOUND AND VIBRATION.2017 李继猛,张云刚,张金凤,谢平.基于自适应随机共振的齿轮微弱冲击故障信号增强提取方法研究.计量学报.2017 何群,郭源耕,王霄,任宗浩,李继猛.基于EEMD与AR建模的风电场风速预测.计量学报.2015 张云刚,王华山,李继猛,魏宇鸿,吴少华,童凯.基于积分吸收光谱技术的NO2气体浓度检测.节能技术.2016 李继猛,谢平,江国乾,林洪彬,杜义浩.基于目标驱动的数字信号处理课程模块化教学改革.教学研究.2016 李继猛,张金凤.Adaptive Multiscale Noise Control Enhanced Stochastic Resonance Method Based on Modified EEMD with Its Application in Bearing Fault Diagnosis.Shock and Vibration.2016 李继猛,张金凤,张云刚,岳宁.基于自适应随机共振和稀疏编码收缩算法的齿轮故障诊断方法.中国机械工程.2016