Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering

2020 ◽  
Vol 89 ◽  
pp. 103434 ◽  
Author(s):  
Javier Diaz-Rozo ◽  
Concha Bielza ◽  
Pedro Larrañaga
Keyword(s):  
Machine Tool ◽  
Mixture Models ◽  
Condition Monitoring ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Tool Condition Monitoring ◽  
Probabilistic Clustering ◽  
Tool Condition

Open Platform for the Integration of Monitoring Applications

2002 ◽  
Author(s):  
Andreas Kahmen ◽  
Manfred Weck
Keyword(s):  
Control System ◽  
Machine Tool ◽  
Real Time ◽  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Integration Platform ◽  
Open Platform ◽  
Tool Condition ◽  
Monitoring Applications ◽  
Monitoring Software

Process and machine tool condition monitoring are the keys to an increasing degree of automation and consequently to an increasing productivity in manufacturing. The realisation of monitoring functionality demands an extension of the control system. The prerequisite for these extensions are open interfaces in the NC-kernel. Nowadays controls with open NC-kernel interfaces are available on the market. However these interfaces are vendor specific solutions that do not allow the reuse of monitoring software in different controls. To overcome these limitations a platform with vendor neutral open real-time interface for the integration of monitoring functionality into the NC-kernel is presented in this paper. Additionally two realisations of the integration platform for different target systems are described.

scholarly journals Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

2012 ◽  
Vol 364 ◽  
pp. 012091 ◽  
Author(s):  
S Sztendel ◽  
C Pislaru ◽  
A P Longstaff ◽  
S Fletcher ◽  
A Myers
Keyword(s):  
Machine Tool ◽  
Real Time ◽  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Time System ◽  
Real Time System ◽  
Tool Condition ◽  
Five Axis

Chasing the Cut: A Measurement Approach for Machine Tool Condition Monitoring

2020 ◽  
pp. 1-1
Author(s):  
Lukasz Huchel ◽  
Thomas C. Krause ◽  
Tomasz Lugowski ◽  
Steven B. Leeb ◽  
Jan Helsen
Keyword(s):  
Machine Tool ◽  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Tool Condition ◽  
Measurement Approach

scholarly journals Ultra low power wireless multi-sensor platform dedicated to machine tool condition monitoring

2020 ◽  
Vol 51 ◽  
pp. 296-301
Author(s):  
Tristan Caroff ◽  
Sebastien Brulais ◽  
Adrien Faucon ◽  
Axel Boness ◽  
Anne Sanz Arrizabalaga ◽  
...  
Keyword(s):  
Low Power ◽  
Machine Tool ◽  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Ultra Low Power ◽  
Tool Condition ◽  
Sensor Platform
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