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Abstract

In this study, a preliminary evaluation was made of the applicability ofthe signalsof the cutting forces, vibration and acoustic emission in

diagnosis of the hardness and microstructure of ausferritic ductile iron and tool edge wear rate during its machining. Tests were performed

on pearlitic-ferritic ductile iron and on three types of ausferritic ductile iron obtained by austempering at 400, 370 and 320⁰C for 180

minutes. Signals of the cutting forces (F), vibration (V) and acoustic emission (AE) were registered while milling each type of the cast iron

with a milling cutter at different degrees of wear. Based on individual signals from all the sensors, numerous measures were determined

such as e.g. the average or maximum signal value. It was found that different measures from all the sensors tested depended on the

microstructure and hardness of the examined material, and on the tool condition. Knowing hardness of the material and the cutting tool

edge condition, it is possible to determine the structure of the material .Simultaneous diagnosis of microstructure, hardness, and the tool

condition is probably feasible, but it would require the application of a diagnostic strategy based on the integration of numerous measures,

e.g. using neural networks.

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Authors and Affiliations

D. Myszka
S. Bombiński

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