On-Line Estimation of Groove Wear in the Minor Cutting Edge for Finish Machining

The paper investigates the effective detection and esdmation of = m v e wear at the minor cutting edge, which has a mtal influence on surface quality in finish-machining. During bar-turning experiments with different cutting conditions, a miniature 3-D accelerometer, mounted in close vicinity to the tool tip, was used to measure the multivariate vibration signal produced by the turning process. The stochastic signal was modelled as autorcgressive vector difference equations, and multiple dispersion analysis was used to quantify the complex interactions among various variables. It was found that the characteristic ingredient of vibration in the thrust direction, complemented by that in the main cutting direction, signifies effectively the critical point at which grooves are king "chiseled out", surface roughness is deteriorating rapidly, and subsequently the finishing-roo1 needs to be replaced. The results are interpreted on a physically sound basis. The results also show that the algorithm developed is a feasible approach to on-line monitoring of minor cutting edge g m v e weu in finish-machining