向玲,李营.风力发电机轴承复合故障特征提取方法研究[J].振动与冲击,2020(09).

张俊,张建群,钟敏,郑近德,李习科.基于PSO-VMD-MCKD方法的风机轴承微弱故障诊断[J].振动.测试与诊断,2020(02).

王靖岳,李建刚,王浩天.采用改进多点最优最小熵反褶积的齿轮箱复合故障特征提取[J].西安交通大学学报,2020(05).

胡爱军,赵军.基于自适应最大相关峭度解卷积的滚动轴承多故障诊断[J].振动与冲击,2019(22).

邓飞跃,强亚文,杨绍普,郝如江,刘永强.一种自适应频率窗经验小波变换的滚动轴承故障诊断方法[J].西安交通大学学报,2018(08).

He Yong,Wang Hong,Xue Hai,Zhang Tao.Research on unknown fault diagnosis of rolling bearings based on parameter-adaptive maximum correlation kurtosis deconvolution.[J].The Review of scientific instruments,2021.

Wang Biao,Lei Yaguo,Li Naipeng,Li Ningbo.A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings[J].IEEE Transactions on Reliability,2020.

Jiankai Xue,Bo Shen.A novel swarm intelligence optimization approach: sparrow search algorithm[J].Systems Science & Control Engineering,2020.

Qin Yi,Li Chengcheng,Cao Folin,Chen Haizhou.A fault dynamic model of high-speed angular contact ball bearings[J].Mechanism and Machine Theory,2020.

Zhang Feibin,Huang Jinfeng,Chu Fulei,Cui Lingli.Mechanism and Method for Outer Raceway Defect Localization of Ball Bearings[J].IEEE Access,2020.

Xuan Lyu,Zhanqi Hu,Haili Zhou,Qiang Wang.Application of improved MCKD method based on QGA in planetary gear compound fault diagnosis[J].Measurement,2019.

Yao Cheng,Zhiwei Wang,Weihua Zhang,Guanhua Huang.Particle swarm optimization algorithm to solve the deconvolution problem for rolling element bearing fault diagnosis[J].ISA Transactions,2019.

Chuancang Ding,Ming Zhao,Jing Lin,Jinyang Jiao.Multi-objective iterative optimization algorithm based optimal wavelet filter selection for multi-fault diagnosis of rolling element bearings[J].ISA Transactions,2019.

Lianhuan Hong,Xiaobo Liu,Hongyan Zuo.Compound fault diagnosis of rotating machinery based on adaptive maximum correlated kurtosis deconvolution and customized multiwavelet transform[J].Measurement Science and Technology,2018.

Wang Fengtao,Liu Chenxi,Su Wensheng,Xue Zhigang,Han Qingkai,Li Hongkun.Combined Failure Diagnosis of Slewing Bearings Based on MCKD-CEEMD-ApEn[J].Shock and Vibration,2018.

Jacek Wodecki,Anna Michalak,Radoslaw Zimroz.Optimal filter design with progressive genetic algorithm for local damage detection in rolling bearings[J].Mechanical Systems and Signal Processing,2018.

Yu Xiao,Dong Fei,Ding Enjie,Wu Shoupeng,Fan Chunyang.Rolling Bearing Fault Diagnosis Using Modified LFDA and EMD With Sensitive Feature Selection[J].IEEE Access,2018.

Akhand Rai,S.H. Upadhyay.A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings[J].Tribology International,2016.

Guiji Tang,Xiaolong Wang,Yuling He.Diagnosis of compound faults of rolling bearings through adaptive maximum correlated kurtosis deconvolution[J].Journal of Mechanical Science and Technology,2016.

Geoff L. McDonald,Qing Zhao,Ming J. Zuo.Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection[J].Mechanical Systems and Signal Processing,2012.

N. Sawalhi,R.B. Randall,H. Endo.The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis[J].Mechanical Systems and Signal Processing,2006.