1. A new two-stage strategy to adaptively design and finely tune the filters for bearing fault-related mode decomposition. (31st March 2023) Authors: Zhang, Boyao; Miao, Yonghao; Lin, Jing; Liu, Zongyang Journal: Measurement Issue: Volume 210(2023) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. A review on the application of blind deconvolution in machinery fault diagnosis. (15th January 2022) Authors: Miao, Yonghao; Zhang, Boyao; Lin, Jing; Zhao, Ming; Liu, Hanyang; Liu, Zongyang; Li, Hao Journal: Mechanical systems and signal processing Issue: Volume 163(2022) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. Adaptive maximum second-order cyclostationarity blind deconvolution and its application for locomotive bearing fault diagnosis. (September 2021) Authors: Zhang, Boyao; Miao, Yonghao; Lin, Jing; Yi, Yinggang Journal: Mechanical systems and signal processing Issue: Volume 158(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
4. An imperfect age-based and condition-based opportunistic maintenance model for a two-unit series system. (October 2021) Authors: Wang, Jingjing; Miao, Yonghao; Yi, Yinggang; Huang, Dagang Journal: Computers & industrial engineering Issue: Volume 160(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
5. Application of an improved maximum correlated kurtosis deconvolution method for fault diagnosis of rolling element bearings. (August 2017) Authors: Miao, Yonghao; Zhao, Ming; Lin, Jing; Lei, Yaguo Journal: Mechanical systems and signal processing Issue: Volume 92(2017) Page Start: 173 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
6. Application of an improved MCKDA for fault detection of wind turbine gear based on encoder signal. (May 2020) Authors: Miao, Yonghao; Zhao, Ming; Liang, Kaixuan; Lin, Jing Journal: Renewable energy Issue: Volume 151(2020) Page Start: 192 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
7. Application of improved double-dictionary K-SVD for compound-fault diagnosis of rolling element bearings. (January 2022) Authors: Zhang, Min; Liang, Kaixuan; Miao, Yonghao; Lin, Jing; Ding, Chuancang Journal: Measurement Issue: Volume 187(2022) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
8. Application of improved reweighted singular value decomposition for gearbox fault diagnosis based on built-in encoder information. (15th January 2021) Authors: Miao, Yonghao; Zhang, Boyao; Yi, Yinggang; Lin, Jing Journal: Measurement Issue: Volume 168(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
9. Application of sparsity-oriented VMD for gearbox fault diagnosis based on built-in encoder information. (April 2020) Authors: Miao, Yonghao; Zhao, Ming; Yi, Yinggang; Lin, Jing Journal: ISA transactions Issue: Volume 99(2020) Page Start: 496 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
10. Deep network-based maximum correlated kurtosis deconvolution: A novel deep deconvolution for bearing fault diagnosis. (15th April 2023) Authors: Miao, Yonghao; Li, Chenhui; Shi, Huifang; Han, Te Journal: Mechanical systems and signal processing Issue: Volume 189(2023) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗