Feature Selection for Tool Condition Monitoring in Turning Processes

2006 ◽  
Vol 526 ◽  
pp. 97-102
Author(s):  
D. Rodríguez Salgado ◽  
I. Cambero ◽  
F.J. Alonso
Keyword(s):  
Neural Networks ◽  
Condition Monitoring ◽  
Industrial Applications ◽  
Tool Condition Monitoring ◽  
Turning Operations ◽  
Additional Signal ◽  
Motor Current ◽  
Tool Condition ◽  
Selection For ◽  
Condition Monitoring System

The aim of the present work is to develop a tool condition monitoring system (TCMS) using sensor fusion and artificial neural networks. Particular attention is paid to the manner in which the most correlated features with tool wear are selected. Experimental results show that the proposed system can reliably detect tool condition in turning operations and is viable for industrial applications. This study leads to the conclusion that the vibration in the feed direction and the motor current signals are best suited for the development of a TCMS than the sound signal, which should be used as an additional signal.

scholarly journals Algorithm of the tool condition monitoring system based on many neural networks

Mechanik ◽  
2017 ◽  
Vol 90 (3) ◽  
pp. 220-223
Author(s):  
Sebastian Bombiński ◽  
Joanna Kossakowska
Keyword(s):  
Neural Networks ◽  
Tool Wear ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Machining Process ◽  
Rbf Neural Networks ◽  
Standard Time ◽  
Tool Condition ◽  
Condition Monitoring System

Presented is a comparison of different methods of estimating tool wear – obtained for group of RBF neural networks, hierarchical methods and the standard time counting. The analysis of the signals from the machining process carried out for three different experiments, clearly demonstrating the effect of presented methods. The results obtained for group of RBF neural networks are similar to results obtained for hierarchical methods.

TOOL CONDITION MONITORING SYSTEM IN SERIAL PRODUCTION CONDITIONS

2020 ◽  
Vol 4 (2) ◽  
pp. 161-168
Author(s):  
V.I. GOLOVIN ◽  
S.Yu. RADCHENKO
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Serial Production ◽  
Tool Condition ◽  
Decision Making System ◽  
Software And Hardware ◽  
Condition Monitoring System ◽  
The Cost

One of the most important tasks of serial and mass production is to maintain the continuity of the technological process in order to reduce equipment downtime and, as a result, the cost of production. One of the systems is the tool condition monitoring system. However, the solutions used today are complex software and hardware systems that are not available for most medium and small productions. The article proposes a system based on a comparative analysis of the applied tool with reference instances. The results of the analysis are sent to the decision-making system, which determines the feasibility of further use of the cutting tool for subsequent machining. An example of an experimental study of milling processing is given. The results obtained show the possibility and rationality of using this model to predict the state of the instrument.

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