{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T01:00:02Z","timestamp":1785200402731,"version":"3.55.0"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2019,8,14]],"date-time":"2019-08-14T00:00:00Z","timestamp":1565740800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,8,14]],"date-time":"2019-08-14T00:00:00Z","timestamp":1565740800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["50975179"],"award-info":[{"award-number":["50975179"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51375289"],"award-info":[{"award-number":["51375289"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51775323"],"award-info":[{"award-number":["51775323"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Manuf"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1007\/s10845-019-01488-7","type":"journal-article","created":{"date-parts":[[2019,8,14]],"date-time":"2019-08-14T17:02:40Z","timestamp":1565802160000},"page":"953-966","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":263,"title":["Tool wear predicting based on multi-domain feature fusion by deep convolutional neural network in milling operations"],"prefix":"10.1007","volume":"31","author":[{"given":"Zhiwen","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianmin","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingtao","family":"Lei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoru","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengqing","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,8,14]]},"reference":[{"issue":"9\u201312","key":"1488_CR1","doi-asserted-by":"publisher","first-page":"3217","DOI":"10.1007\/s00170-018-2420-0","volume":"98","author":"F Aghazadeh","year":"2018","unstructured":"Aghazadeh, F., Tahan, A., & Thomas, M. (2018). Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process. The International Journal of Advanced Manufacturing Technology,98(9\u201312), 3217\u20133227.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"1488_CR2","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1214\/09-SS054","volume":"4","author":"S Arlot","year":"2010","unstructured":"Arlot, S., & Celisse, A. (2010). A survey of cross-validation procedures for model selection. Statistics Surveys,4, 40\u201379.","journal-title":"Statistics Surveys"},{"issue":"2","key":"1488_CR3","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1007\/s10845-013-0774-6","volume":"26","author":"T Benkedjouh","year":"2015","unstructured":"Benkedjouh, T., Medjaher, K., Zerhouni, N., & Rechak, S. (2015). Health assessment and life prediction of cutting tools based on support vector regression. Journal of Intelligent Manufacturing,26(2), 213\u2013223.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"1488_CR100","doi-asserted-by":"crossref","unstructured":"Chen, Y., Jin, Y., & Jiri, G. (2018). Predicting tool wear with multi-sensor data using deep belief networks. The International Journal of Advanced Manufacturing Technology, 99(5\u20138), 1917\u20131926.","DOI":"10.1007\/s00170-018-2571-z"},{"issue":"5","key":"1488_CR4","doi-asserted-by":"publisher","first-page":"739","DOI":"10.1016\/S0890-6955(99)00084-X","volume":"40","author":"DE Dimla Sr","year":"2000","unstructured":"Dimla, D. E., Sr., & Lister, P. M. (2000). On-line metal cutting tool condition monitoring. I: Force and vibration analyses. International Journal of Machine Tools and Manufacture,40(5), 739\u2013768.","journal-title":"International Journal of Machine Tools and Manufacture"},{"key":"1488_CR5","doi-asserted-by":"publisher","first-page":"1073","DOI":"10.1016\/S0890-6955(99)00122-4","volume":"40","author":"DE Dimla Snr","year":"2000","unstructured":"Dimla Snr, D. E. (2000). Sensor signals for tool-wear monitoring in metal cutting operations\u2014A review of methods. International Journal of Machine Tools and Manufacture,40, 1073\u20131098.","journal-title":"International Journal of Machine Tools and Manufacture"},{"key":"1488_CR6","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1016\/j.ymssp.2015.04.019","volume":"66\u201367","author":"JA Duro","year":"2016","unstructured":"Duro, J. A., Padget, J. A., Bowen, C. R., Kim, H. A., & Nassehi, A. (2016). Multi-sensor data fusion framework for CNC machining monitoring. Mechanical Systems and Signal Processing,66\u201367, 505\u2013520.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"6","key":"1488_CR7","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1016\/0890-6955(95)00058-5","volume":"36","author":"TI El-Wardany","year":"1996","unstructured":"El-Wardany, T. I., Gao, D., & Elbestawi, M. A. (1996). Tool condition monitoring in drilling using vibration signature analysis. International Journal of Machine Tools and Manufacture,36(6), 687\u2013711.","journal-title":"International Journal of Machine Tools and Manufacture"},{"key":"1488_CR8","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1016\/j.engappai.2017.07.024","volume":"65","author":"Y Fu","year":"2017","unstructured":"Fu, Y., Zhang, Y., Gao, Y., Gao, H., Mao, T., Zhou, H. M., et al. (2017). Machining vibration states monitoring based on image representation using convolutional neural networks. Engineering Applications of Artificial Intelligence,65, 240\u2013251.","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"1488_CR9","doi-asserted-by":"publisher","first-page":"902","DOI":"10.1016\/j.ymssp.2017.05.028","volume":"98","author":"PE Garc\u00eda","year":"2018","unstructured":"Garc\u00eda, P. E., & N\u00fa\u00f1ez L\u00f3pez, P. J. (2018). Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations. Mechanical Systems and Signal Processing,98, 902\u2013919.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"1","key":"1488_CR10","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1016\/j.ymssp.2005.10.010","volume":"21","author":"N Ghosh","year":"2007","unstructured":"Ghosh, N., Ravi, Y. B., Patra, A., Mukhopadhyay, S., Paul, S., Mohanty, A. R., et al. (2007). Estimation of tool wear during CNC milling using neural network-based sensor fusion. Mechanical Systems and Signal Processing,21(1), 466\u2013479.","journal-title":"Mechanical Systems and Signal Processing"},{"key":"1488_CR11","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.ymssp.2016.08.002","volume":"89","author":"P Gierlak","year":"2016","unstructured":"Gierlak, P., Burghardt, A., Szybicki, D., Szuster, M., & Muszy\u0144ska, M. (2016). On-line manipulator tool condition monitoring based on vibration analysis. Mechanical Systems and Signal Processing,89, 14\u201326.","journal-title":"Mechanical Systems and Signal Processing"},{"key":"1488_CR12","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton, G. E., & Salakhutdinov, R. R. (2006). Reducing the dimensionality of data with neural networks. Science,313, 504\u2013507.","journal-title":"Science"},{"issue":"3","key":"1488_CR13","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1016\/j.ijmachtools.2006.06.011","volume":"47","author":"SN Huang","year":"2007","unstructured":"Huang, S. N., Tan, K. K., Wong, Y. S., De Silva, C. W., Goh, H. L., & Tan, W. W. (2007). Tool wear detection and fault diagnosis based on cutting force monitoring. International Journal of Machine Tools and Manufacture,47(3), 444\u2013451.","journal-title":"International Journal of Machine Tools and Manufacture"},{"key":"1488_CR14","doi-asserted-by":"publisher","first-page":"1873","DOI":"10.1007\/s10845-016-1221-2","volume":"29","author":"K Javed","year":"2016","unstructured":"Javed, K., Gouriveau, R., Li, X., & Zerhouni, N. (2016). Tool wear monitoring and prognostics challenges: A comparison of connectionist methods toward an adaptive ensemble model. Journal of Intelligent Manufacturing,29, 1873\u20131890.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"1488_CR101","doi-asserted-by":"crossref","unstructured":"Karandikar, J., McLeay, T., Turner S., Schmitz, T. (2015). Tool wear monitoring using naive Bayes classifiers. The International Journal of Advanced Manufacturing Technology, 77(9), 1613\u20131626.","DOI":"10.1007\/s00170-014-6560-6"},{"key":"1488_CR15","unstructured":"Keskar, N. S., Mudigere, D., Nocedal, J., Smelyanskiy, M., & Tang, P. T. P. (2016). On large-batch training for deep learning: Generalization gap and sharp minima. arXiv preprint \narXiv:1609.04836\n\n."},{"key":"1488_CR16","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1016\/j.ymssp.2017.11.021","volume":"104","author":"D Kong","year":"2018","unstructured":"Kong, D., Chen, Y., & Li, N. (2018). Gaussian process regression for tool wear prediction. Mechanical Systems and Signal Processing,104, 556\u2013574.","journal-title":"Mechanical Systems and Signal Processing"},{"key":"1488_CR17","unstructured":"Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet classification with deep convolutional neural networks. In 21th annual conference on neural information processing systems (NIPS). Lake Tahoe, USA, December 3\u20138."},{"issue":"1","key":"1488_CR18","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.ijmachtools.2004.06.016","volume":"45","author":"E Kuljanic","year":"2005","unstructured":"Kuljanic, E., & Sortino, M. (2005). TWEM, a method based on cutting forces-monitoring tool wear in face milling. International Journal of Machine Tools and Manufacture,45(1), 29\u201334.","journal-title":"International Journal of Machine Tools and Manufacture"},{"issue":"11","key":"1488_CR19","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"YL Lecun","year":"1998","unstructured":"Lecun, Y. L., Bottou, L., Bengio, Y., & Haffner, P. (1998a). Gradient-based learning applied to document recognition. Proceedings of the IEEE,86(11), 2278\u20132324.","journal-title":"Proceedings of the IEEE"},{"issue":"1","key":"1488_CR20","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1007\/3-540-49430-8_2","volume":"1524","author":"Y Lecun","year":"1998","unstructured":"Lecun, Y., Bottou, L., Orr, G. B., & M\u00fcller, K. R. (1998b). Efficient backprop. Lecture Notes in Computer Science,1524(1), 9\u201350.","journal-title":"Lecture Notes in Computer Science"},{"key":"1488_CR21","unstructured":"Li, X., Lim, B. S., Zhou, J. H., & Huang, S. (2009). Fuzzy neural network modelling for tool wear estimation in dry milling operation. In Annual conference of the prognostics and health management society (pp. 1\u201311). PHM Society."},{"issue":"8","key":"1488_CR22","first-page":"8605","volume":"4","author":"R Mali","year":"2017","unstructured":"Mali, R., Telsang, M. T., & Gupta, T. V. K. (2017). Real time tool wear condition monitoring in hard turning of Inconel 718 using sensor fusion system. Materials Today: Proceedings,4(8), 8605\u20138612.","journal-title":"Materials Today: Proceedings"},{"key":"1488_CR23","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1007\/s10845-015-1180-z","volume":"29","author":"J Morgan","year":"2018","unstructured":"Morgan, J., & O\u2019Donnell, G. E. (2018). Cyber physical process monitoring systems. Journal of Intelligent Manufacturing,29, 1317\u20131328.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"1488_CR24","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/j.jmapro.2017.11.014","volume":"31","author":"V Pandiyan","year":"2018","unstructured":"Pandiyan, V., Caesarendra, W., Tjahjowidodo, T., & Tan, H. H. (2018). In-process tool condition monitoring in compliant abrasive belt grinding process using support vector machine and genetic algorithm. Journal of Manufacturing Processes,31, 199\u2013213.","journal-title":"Journal of Manufacturing Processes"},{"issue":"6","key":"1488_CR25","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1007\/s10845-009-0249-y","volume":"21","author":"S Purushothaman","year":"2010","unstructured":"Purushothaman, S. (2010). Tool wear monitoring using artificial neural network based on extended Kalman filter weight updation with transformed input patterns. Journal of Intelligent Manufacturing,21(6), 717\u2013730.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"7\u20138","key":"1488_CR26","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1007\/s00170-004-2038-2","volume":"26","author":"AG Rehorn","year":"2005","unstructured":"Rehorn, A. G., Jiang, J., & Orban, P. E. (2005). State-of-the-art methods and results in tool condition monitoring: A review. The International Journal of Advanced Manufacturing Technology,26(7\u20138), 693\u2013710.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"1488_CR27","unstructured":"Ruder, S. (2016). An overview of gradient descent optimization algorithms. arXiv preprint \narXiv:1609.04747\n\n."},{"key":"1488_CR28","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1016\/j.procir.2015.06.043","volume":"33","author":"M Salehi","year":"2015","unstructured":"Salehi, M., Albertelli, P., Goletti, M., Ripamonti, F., Tomasini, G., & Monno, M. (2015). Indirect model based estimation of cutting force and tool tip vibrational behavior in milling machines by sensor fusion. Procedia CIRP,33, 239\u2013244.","journal-title":"Procedia CIRP"},{"key":"1488_CR29","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.ymssp.2011.10.018","volume":"28","author":"DA Tobon-Mejia","year":"2012","unstructured":"Tobon-Mejia, D. A., Medjaher, K., & Zerhouni, N. (2012). CNC machine tool\u2019s wear diagnostic and prognostic by using dynamic Bayesian networks. Mechanical Systems and Signal Processing,28, 167\u2013182.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"6","key":"1488_CR30","doi-asserted-by":"publisher","first-page":"1403","DOI":"10.1007\/s10845-013-0738-x","volume":"25","author":"G Wang","year":"2014","unstructured":"Wang, G., Guo, Z., & Qian, L. (2014). Online incremental learning for tool condition classification using modified fuzzy ARTMAP network. Journal of Intelligent Manufacturing,25(6), 1403\u20131411.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"C","key":"1488_CR31","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.rcim.2016.05.010","volume":"45","author":"J Wang","year":"2017","unstructured":"Wang, J., Xie, J., Zhao, R., Zhang, L., & Duan, L. (2017). Multisensory fusion based virtual tool wear sensing for ubiquitous manufacturing. Robotics and Computer Integrated Manufacturing,45(C), 47\u201358.","journal-title":"Robotics and Computer Integrated Manufacturing"},{"key":"1488_CR32","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.asoc.2018.03.043","volume":"68","author":"J Wu","year":"2018","unstructured":"Wu, J., Su, Y., Cheng, Y., Shao, X., Deng, C., & Liu, C. (2018). Multi-sensor information fusion for remaining useful life prediction of machining tools by adaptive network based fuzzy inference system. Applied Soft Computing,68, 13\u201323.","journal-title":"Applied Soft Computing"},{"issue":"1\u20134","key":"1488_CR33","first-page":"1","volume":"91","author":"J Yu","year":"2017","unstructured":"Yu, J., Liang, S., Tang, D., & Liu, H. (2017). A weighted hidden Markov model approach for continuous-state tool wear monitoring and tool life prediction. International Journal of Advanced Manufacturing Technology,91(1\u20134), 1\u201311.","journal-title":"International Journal of Advanced Manufacturing Technology"},{"key":"1488_CR34","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1016\/j.ymssp.2017.06.022","volume":"100","author":"W Zhang","year":"2018","unstructured":"Zhang, W., Li, C. H., Peng, G. L., Chen, Y. H., & Zhang, Z. J. (2018). A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load. Mechanical Systems and Signal Processing,100, 439\u2013453.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"5","key":"1488_CR35","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1007\/s10845-015-1112-y","volume":"26","author":"KF Zhang","year":"2015","unstructured":"Zhang, K. F., Yuan, H. Q., & Nie, P. (2015). A method for tool condition monitoring based on sensor fusion. Journal of Intelligent Manufacturing,26(5), 1011\u20131026.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"2","key":"1488_CR36","doi-asserted-by":"publisher","first-page":"273","DOI":"10.3390\/s17020273","volume":"17","author":"R Zhao","year":"2017","unstructured":"Zhao, R., Yan, R., Wang, J., & Mao, K. (2017). Learning to monitor machine health with convolutional bi-directional LSTM networks. Sensors,17(2), 273.","journal-title":"Sensors"},{"issue":"5\u20138","key":"1488_CR37","doi-asserted-by":"publisher","first-page":"2509","DOI":"10.1007\/s00170-018-1768-5","volume":"96","author":"Y Zhou","year":"2018","unstructured":"Zhou, Y., & Xue, W. (2018). Review of tool condition monitoring methods in milling processes. International Journal of Advanced Manufacturing Technology,96(5\u20138), 2509\u20132523.","journal-title":"International Journal of Advanced Manufacturing Technology"},{"issue":"7","key":"1488_CR38","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1016\/j.ijmachtools.2009.02.003","volume":"49","author":"KP Zhu","year":"2009","unstructured":"Zhu, K. P., Wong, Y. S., & Hong, G. S. (2009). Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results. International Journal of Machine Tools and Manufacture,49(7), 537\u2013553.","journal-title":"International Journal of Machine Tools and Manufacture"}],"container-title":["Journal of Intelligent Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-019-01488-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10845-019-01488-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-019-01488-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,12]],"date-time":"2020-08-12T23:34:41Z","timestamp":1597275281000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10845-019-01488-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,14]]},"references-count":40,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,4]]}},"alternative-id":["1488"],"URL":"https:\/\/doi.org\/10.1007\/s10845-019-01488-7","relation":{},"ISSN":["0956-5515","1572-8145"],"issn-type":[{"value":"0956-5515","type":"print"},{"value":"1572-8145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,14]]},"assertion":[{"value":"2 February 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 August 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 August 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}