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Original Articles

A COMPARATIVE STUDY OF FEATURE SELECTION FOR HIDDEN MARKOV MODEL-BASED MICRO-MILLING TOOL WEAR MONITORING

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Pages 348-369 | Published online: 12 Sep 2008

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Wen-An Yang, Qiang Zhou & Kwok-Leung Tsui. (2016) Differential evolution-based feature selection and parameter optimisation for extreme learning machine in tool wear estimation. International Journal of Production Research 54:15, pages 4703-4721.
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Articles from other publishers (31)

Maryam Assafo, Jost Philipp Städter, Tenia Meisel & Peter Langendörfer. (2023) On the Stability and Homogeneous Ensemble of Feature Selection for Predictive Maintenance: A Classification Application for Tool Condition Monitoring in Milling. Sensors 23:9, pages 4461.
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Ayman Mohamed, Mahmoud Hassan, Rachid M’Saoubi & Helmi Attia. (2022) Tool Condition Monitoring for High-Performance Machining Systems—A Review. Sensors 22:6, pages 2206.
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Oluwaseyi Paul Babalola & Vipin Balyan. (2021) WiFi Fingerprinting Indoor Localization Based on Dynamic Mode Decomposition Feature Selection with Hidden Markov Model. Sensors 21:20, pages 6778.
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Guo Hao & Zhu Kunpeng. (2020) Pyramid LSTM auto-encoder for tool wear monitoring. Pyramid LSTM auto-encoder for tool wear monitoring.
Yaw Agyabeng-Mensah, Ebenezer Afum, Carin Agnikpe, Jiaxin Cai, Esther Ahenkorah & Essel Dacosta. (2020) Exploring the mediating influences of total quality management and just in time between green supply chain practices and performance. Journal of Manufacturing Technology Management 32:1, pages 156-175.
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Maciej Kusy, Roman Zajdel, Jacek Kluska & Tomasz Zabinski. (2020) Fusion of Feature Selection Methods for Improving Model Accuracy in the Milling Process Data Classification Problem. Fusion of Feature Selection Methods for Improving Model Accuracy in the Milling Process Data Classification Problem.
Boya Niu, Jie Sun & Bin Yang. (2020) Multisensory based tool wear monitoring for practical applications in milling of titanium alloy. Materials Today: Proceedings 22, pages 1209-1217.
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Roman Zajdel, Maciej Kusy, Jacek Kluska & Tomasz Zabinski. 2020. Artificial Intelligence and Soft Computing. Artificial Intelligence and Soft Computing 280 291 .
Stephen Adams & Peter A. Beling. (2017) A survey of feature selection methods for Gaussian mixture models and hidden Markov models. Artificial Intelligence Review 52:3, pages 1739-1779.
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Meng Hu, Weiwei Ming, Qinglong An & Ming Chen. (2019) Tool wear monitoring in milling of titanium alloy Ti–6Al–4 V under MQL conditions based on a new tool wear categorization method. The International Journal of Advanced Manufacturing Technology 104:9-12, pages 4117-4128.
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Weijian Li & Tongshun Liu. (2019) Time varying and condition adaptive hidden Markov model for tool wear state estimation and remaining useful life prediction in micro-milling. Mechanical Systems and Signal Processing 131, pages 689-702.
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YeongGwang Oh, Kasin Ransikarbum, Moise Busogi, Daeil Kwon & Namhun Kim. (2019) Adaptive SVM-based real-time quality assessment for primer-sealer dispensing process of sunroof assembly line. Reliability Engineering & System Safety 184, pages 202-212.
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Zhengyou Xie, Jianguang Li & Yong Lu. (2018) Feature selection and a method to improve the performance of tool condition monitoring. The International Journal of Advanced Manufacturing Technology 100:9-12, pages 3197-3206.
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D S Ye, Y H J Fuh, Y J Zhang, G S Hong & K P Zhu. (2018) Defects Recognition in Selective Laser Melting with Acoustic Signals by SVM Based on Feature Reduction. IOP Conference Series: Materials Science and Engineering 436, pages 012020.
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Wen-An Yang, Maohua Xiao, Wei Zhou, Yu Guo, Wenhe Liao & Gang Shen. (2016) Trace Ratio Criterion-Based Kernel Discriminant Analysis for Fault Diagnosis of Rolling Element Bearings Using Binary Immune Genetic Algorithm. Shock and Vibration 2016, pages 1-15.
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Yibo Li, Yuxiang Zhang, Huiyu Zhu, Rongxin Yan, Yuanyuan Liu, Liying Sun & Zhoumo Zeng. (2015) Recognition Algorithm of Acoustic Emission Signals Based on Conditional Random Field Model in Storage Tank Floor Inspection Using Inner Detector. Shock and Vibration 2015, pages 1-9.
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Tahar Boukra & Abdesselam Lebaroud. (2014) Identifying new prognostic features for remaining useful life prediction. Identifying new prognostic features for remaining useful life prediction.
Omid Geramifard, Jian-Xin Xu, Jun-Hong Zhou & Xiang Li. (2014) Multimodal Hidden Markov Model-Based Approach for Tool Wear Monitoring. IEEE Transactions on Industrial Electronics 61:6, pages 2900-2911.
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Emel Kuram & Babur Ozcelik. 2014. Modern Mechanical Engineering. Modern Mechanical Engineering 325 365 .
Emel Kuram & Babur Ozcelik. (2013) Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill. Measurement 46:6, pages 1849-1864.
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Chien-Wei Hung & Ming-Chyuan Lu. (2012) Model development for tool wear effect on AE signal generation in micromilling. The International Journal of Advanced Manufacturing Technology 66:9-12, pages 1845-1858.
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Guofeng Wang & Xiaoliang Feng. (2013) Tool wear state recognition based on linear chain conditional random field model. Engineering Applications of Artificial Intelligence 26:4, pages 1421-1427.
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Chia-Liang Yen, Ming-Chyuan Lu & Jau-Liang Chen. (2013) Applying the self-organization feature map (SOM) algorithm to AE-based tool wear monitoring in micro-cutting. Mechanical Systems and Signal Processing 34:1-2, pages 353-366.
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Omid Geramifard, Jian-Xin Xu, Jun-Hong Zhou & Xiang Li. (2012) A Physically Segmented Hidden Markov Model Approach for Continuous Tool Condition Monitoring: Diagnostics and Prognostics. IEEE Transactions on Industrial Informatics 8:4, pages 964-973.
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Ming-Chyuan Lu & Bing-Syun Wan. (2012) Study of high-frequency sound signals for tool wear monitoring in micromilling. The International Journal of Advanced Manufacturing Technology.
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Omid Geramifard, Jian-Xin Xu, Jun-Hong Zhou, Xiang Li & Oon Peen Gan. (2012) Feature selection for tool wear monitoring: A comparative study. Feature selection for tool wear monitoring: A comparative study.
Zhu Kunpeng, Wong Yoke San & Hong Geok Soon. 2012. Mechatronics and Manufacturing Engineering. Mechatronics and Manufacturing Engineering 115 157 .
Omid Geramifard, Jian-Xin Xu, Tan Sicong, Jun-Hong Zhou & Xiang Li. (2011) A multi-modal hidden Markov model based approach for continuous health assessment in machinery systems. A multi-modal hidden Markov model based approach for continuous health assessment in machinery systems.
Zhao Dong. 2011. Intelligent Diagnosis and Prognosis of Industrial Networked Systems. Intelligent Diagnosis and Prognosis of Industrial Networked Systems 263 277 .
Omid Geramifard, Jian-Xin Xu, Jun-Hong Zhou & Xiang Li. (2011) Continuous health condition monitoring: A single Hidden Semi-Markov Model approach. Continuous health condition monitoring: A single Hidden Semi-Markov Model approach.
Jun-Hong Zhou, Chee Khiang Pang, Zhao-Wei Zhong & Frank L. Lewis. (2011) Tool Wear Monitoring Using Acoustic Emissions by Dominant-Feature Identification. IEEE Transactions on Instrumentation and Measurement 60:2, pages 547-559.
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