References
- X. Liu, Intelligent machining technology in cutting process, JME 54 (16), 45 (2018). DOI: 10.3901/JME.2018.16.045.
- Y. Zhu, Tool Fault Diagnosis based on Wavelet Neural Networks, Master’s thesis, Southwest Jiaotong University, 2005.,
- H. Luo, D. Zhang, and M. Luo, Tool wear and remaining useful life estimation of difficult-to-machine aerospace alloys: a review, China Mech. Engng. 32 (22), 2647 (2021).
- Y. Chang, L. Wei, and R. Wang, A review of data-driven methods for predicting remaining tool life, Electr. Technol. Software Engng. (19), 193 (2020).
- N. Li et al., Force-based tool condition monitoring for turning process using v-support vector regression, Int. J. Adv. Manuf. Technol. 91 (1–4), 351 (2017). DOI: 10.1007/s00170-016-9735-5.
- M. Ferguson et al., A generalized method for featurization of manufacturing signals, with application to tool condition monitoring, presented at, ASME 2017 international design engineering technical conferences and computers and information in engineering conference, 2017., Cleveland, Ohio, USA, 6–9, Aug. DOI: 10.1115/DETC2017-67987.
- D. Gao et al., Multi-scale statistical signal processing of cutting force in cutting tool condition monitoring, Int. J. Adv. Manuf. Technol. 80 (9–12), 1843 (2015). DOI: 10.1007/s00170-015-7116-0.
- L. Guo et al., Research on bearing condition monitoring based on deep learning, J. Vibrat. Shock. 35 (12), 166 (2016).
- J. Zhang, Particle learning and gated recurrent neural network for online tool wear diagnosis and prognosis, Ph.D. dissertation, North Carolina State University, 2018.
- W. Dai et al., Prediction model of milling cutter wear status based on deep learning, China Mech. Engng. 31 (17), 2071 (2020).
- D. Chen et al., A method for predicting spindle rotation accuracy using vibration, Sci. Sin.-Tech. 50 (6), 819 (2020). DOI: 10.1360/SST-2019-0363.
- J. Li, Industrial Big Data (Machinery Industry Press, Beijing, China 2015).
- Y. Tao, G. Zeng, and N. Li, Tool wear evaluation based on decision tree regression and adaboost algorithm, Comp. Sys. Appl. 26 (12), 212 (2017).
- F. Gers, J. Schmidhuber, and F. Cummins, Learning to forget: continual prediction with LSTM, Neural Comput. 12 (10), 2451 (2000). DOI: 10.1162/089976600300015015.