A weighted hidden Markov model approach for continuous-state tool wear monitoring and tool life prediction

2016 ◽  
Vol 91 (1-4) ◽  
pp. 201-211 ◽  
Author(s):  
Jinsong Yu ◽  
Shuang Liang ◽  
Diyin Tang ◽  
Hao Liu
Keyword(s):  
Tool Wear ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Tool Life ◽  
Life Prediction ◽  
Hidden Markov ◽  
Tool Wear Monitoring ◽  
Continuous State ◽  
Wear Monitoring ◽  
Model Approach

Hidden Markov Model-based Tool Wear Monitoring in Turning

2002 ◽  
Vol 124 (3) ◽  
pp. 651-658 ◽  
Author(s):  
Litao Wang ◽  
Mostafa G. Mehrabi ◽  
Elijah Kannatey-Asibu,
Keyword(s):  
Tool Wear ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Training Data ◽  
Tool Wear Monitoring ◽  
Modeling Framework ◽  
Detection Rates ◽  
Feature Vectors ◽  
Wear Monitoring

This paper presents a new modeling framework for tool wear monitoring in machining processes using hidden Markov models (HMMs). Feature vectors are extracted from vibration signals measured during turning. A codebook is designed and used for vector quantization to convert the feature vectors into a symbol sequence for the hidden Markov model. A series of experiments are conducted to evaluate the effectiveness of the approach for different lengths of training data and observation sequence. Experimental results show that successful tool state detection rates as high as 97% can be achieved by using this approach.

Multimodal Hidden Markov Model-Based Approach for Tool Wear Monitoring

2014 ◽  
Vol 61 (6) ◽  
pp. 2900-2911 ◽  
Author(s):  
Omid Geramifard ◽  
Jian-Xin Xu ◽  
Jun-Hong Zhou ◽  
Xiang Li
Keyword(s):  
Tool Wear ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Tool Wear Monitoring ◽  
Model Based ◽  
Wear Monitoring

Research of Tool Wear Monitoring and Tool Life Prediction Models

2020 ◽  
Author(s):  
Qilin Xiang ◽  
Aibo Xu ◽  
Ling Yuan ◽  
Xiang Hu ◽  
Liwei Luo ◽  
...  
Keyword(s):  
Tool Wear ◽  
Tool Life ◽  
Life Prediction ◽  
Prediction Models ◽  
Tool Wear Monitoring ◽  
Wear Monitoring

scholarly journals The Population Biology of Bacterial Plasmids: A Hidden Markov Model Approach

Genetics ◽  
2006 ◽  
Vol 176 (2) ◽  
pp. 957-968 ◽  
Author(s):  
José M. Ponciano ◽  
Leen De Gelder ◽  
Eva M. Top ◽  
Paul Joyce
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Population Biology ◽  
Hidden Markov ◽  
Bacterial Plasmids ◽  
Model Approach
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