发表论文情况： [1] Ou, J. Li, H., Huang, G. Yang， G. (2020).Intelligent analysis of tool wear state using stacked denoising autoencoder with online sequential-extreme learning machine [J]. Measurement, 2020, 167.（SCI源刊）； [2] Ou, J. Li, H., Huang, G. (2020). A novel order analysis and stacked sparse auto-encoder feature learning method for milling tool wear condition monitoring [J], Sensors, 2020, 10(20).（SCI源刊）； [3] Ou, J. Li, H., Huang, G. (2021). Tool wear recognition based on deep kernel autoencoder with multichannel signals fusion [J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70, 1-9. （SCI源刊）； [4] Ou, J. Li, H., Liu, B. (2022). Deep transfer residual variational autoencoder with multi-sensors fusion for tool condition monitoring in impeller machining [J], Measurement, 2022, 11(30).（SCI源刊）； [5] Ou, J. Li, H., Wang, Z. (2022). Tool wear recognition and signals labeling with small cross labeled samples in impeller machining [J]. The International Journal of Advanced Manufacturing Technology, 2022. 123: 3845-3856.（SCI源刊）； [6] Li, H., Ou, J. Zhao, X. (2021). Intelligent identification of rotating stall for centrifugal compressor based on pressure pulsation signals and SDKAE network [J]. Journal of Dynamics, Monitoring and Diagnostics, 2022. 1(3), 169–175。 |
