Date of download: 11/12/2016 Copyright © ASME. All rights reserved. From: Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model J. Manuf. Sci. Eng. 2012;134(3): doi: / AGMM-based prognostics system for tool performance degradation assessment Figure Legend:

Date of download: 11/12/2016 Copyright © ASME. All rights reserved. From: Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model J. Manuf. Sci. Eng. 2012;134(3): doi: / Flow chart of AGMM algorithm Figure Legend:

Date of download: 11/12/2016 Copyright © ASME. All rights reserved. From: Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model J. Manuf. Sci. Eng. 2012;134(3): doi: / Distance calculation between two Gaussian components Figure Legend:

Date of download: 11/12/2016 Copyright © ASME. All rights reserved. From: Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model J. Manuf. Sci. Eng. 2012;134(3): doi: / Inconsistent degradation patterns of RMS of AE and vibration sensors on table for the run cases 1–4 from subgroup G11: (a) RMS and (b) WE1 Figure Legend:

Date of download: 11/12/2016 Copyright © ASME. All rights reserved. From: Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model J. Manuf. Sci. Eng. 2012;134(3): doi: / Scatter plot of training data with two principal components along with data distribution estimation of GMM for four baseline data sets: (a) Databsg11, (b) Databsg12, (c) Databsg21, and (d) Databsg22 Figure Legend:

Date of download: 11/12/2016 Copyright © ASME. All rights reserved. From: Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model J. Manuf. Sci. Eng. 2012;134(3): doi: / LLP monitoring charts for full life of tools from four subgroups: (a) G11, (b) G12, (c) G21, and (d) G22 Figure Legend:

Date of download: 11/12/2016 Copyright © ASME. All rights reserved. From: Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model J. Manuf. Sci. Eng. 2012;134(3): doi: / KL-divergence charts for the run case 1 at different running sample time points: (a) the ninth running sample is finished, and (b) the last running sample is finished Figure Legend:

Date of download: 11/12/2016 Copyright © ASME. All rights reserved. From: Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model J. Manuf. Sci. Eng. 2012;134(3): doi: / KL-divergence charts for the run case 3 at different running sample time points: (a) the ninth running sample is finished, and (b) the last running sample is finished Figure Legend: