INVESTIGATION OF TOOL WEAR, FRACTURE, AND CHIP FORMATION IN METAL CUTTING USING ACOUSTIC EMISSION.

摘要

One of the prime objectives in metal cutting research is the detection of tool wear or failure so that the part size and quality of produts are assured and downtime due to unexpected tool failure can be prevented. Moreover, chip control in a turning operation is another serious problem that must be addressed in operating an unmanned machine tool. The sensitivity of the acoustic emission (AE) signal to the deformation mechanisms, friction process, and fracture process make it an appropriate tool for studying and detecting the wear and the breakage as well as the chipping of a cutting tool and for monitoring the chip formation during metal cutting. Experiments were conducted on a lathe using conventional carbide insert tools under realistic cutting conditions.;To detect the breakage and the chipping of a cutting tool during machining, tangential force and feed force were also measured for comparisons. The RMS value of burst AE signal due to tool fracture is found as a function of fracture area and cutting load. The magnitude of tangential force drop shows a linear relationship with fractured length along the cutting edge. Both mean RMS energy of AE signal and feed force level are sensitive to the chipping of a cutting tool.;The event count of AE signals shows good correlation to chip breaking frequency. The rate increases with increasing feed rate. When congestation or entangling occurs due to continuous chip formation, a significant amount of acoustic emission generates.;The AE- cutting tool system used in this investigation was calibrated by using a pencil lead break test as well as a pulser/system calibrator. An AE signal attenuation factor of from 4 to 5 was identified during signal propagating from workpiece to an insert when the cutting edge contacts with workpiece. . . . (Author's abstract exceeds stipulated maximum length. Discontinued here with permission of author.) UMI.;A method was developed to analyze AE signals containing noise due to chip breaking based on different characteristics of AE signals generated during normal cutting and chip breakage. The mean RMS values of AE signals for various degrees of tool wear are presented, and the general trend of increasing RMS value with increasing flank wear is seen. The skew and kurtosis analysis of the RMS acoustic emission signal shows the sensitivity to the combined effect of flank and crater wear. The skew illustrates an increasing trend with increasing tool wear while the kurtosis decreases with elapsed time. The spectral characteristics of AE signal generated during machining is also illustrated, and the power spectrum amplitude increases with increasing tool wear.