MULTISENSORING TOOL WEAR ESTIMATION IN FACE MILLING WITH NEURAL NETWORKS

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MOSTAFA POURASL A.; RAZFAR M.R.

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Paper Information

Journal: AMIRKABIR Year:2006 | Volume:17 | Issue:64-B (TOPICS IN: MECHANICAL ENGINEERING & INDUSTRIAL ENGINEERING) Page(s): 11-20

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Title

MULTISENSORING TOOL WEAR ESTIMATION IN FACE MILLING WITH NEURAL NETWORKS

Author(s)

MOSTAFA POURASL A. | RAZFAR M.R. | Issue Writer Certificate

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Abstract

Controlling system state is a purpose in system automation. Monitoring of tool wear is the same in machining process. Dimensional accuracy, surface quality of work, machining economy, machine tools life and machining forces were influenced by tool wear. So estimating the tool wear without stopping the operation can be a monitoring method. In this paper an on-line multisensoring approach for tool wear estimation in face milling proposed. Measuring of forces and motor current simultaneously is used. Many experimental tests have been done in different machining conditions and a back propagation neural network (bp) has been designed. This neural network can estimate the tool wear amount with a high accuracy by measuring of machining forces and motor current simultaneously. This method can be used in controlling and monitoring of machining process.

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