Pattern-recognition analysis of sound radiation in metal cutting.

Pattern-recognition analysis of sound radiation was developed as a basis for monitoring the metal-cutting process. The sound-pressure signals radiated during cutting under fixed conditions were recorded using a sharp tool, a worn tool and a broken tool. A round bar of heat-treated AISI 4340 steel was machined in cylindrical turning, using a titanium-carbide-coated cutting tool. The spectral components in the 0-10 kHz range were used as features. Using resubstitution, signals coming from sharp and worn tools were easily distinguished, resulting in a 100% classification with just two features, being the average of the low (0-5 kHz) and high (5-10 kHz) frequency ranges. With tool breakage, two acceptable classifications were obtained using independent testing, the first with a performance of 100%, 75% and 100% for sharp, worn and breakage signals respectively, using nine features, and the second with 80%, 88% and 80%, using eight features. [ABSTRACT FROM AUTHOR]