The relationship between acoustic emission signals and cutting phenomena in turning process

A new approach for detection of wear mechanisms and determination of tool life in turning using acoustic emission

“…Machining [14] 70 to 115 White layer [15] > 60 Isothermal phase transformation [16] 250 to 350 Mild adhesive wear [17] 0 to 120 Severe adhesive wear [17] 1000 to 1500 Adhesion and dragging [18] 25 to 110 Movement of dislocations [13] 10 to 220 Particle interaction [19] 120 to 350 Abrasive wear [8,13] 200 to 1000 Crack propagation [20,21] 350 to 550 Phase transformation [16] 350 to 550 Accommodation of vacancies [22] 220 to 380…”

“…In spite of that, AE is a promising technique for monitoring cutting tool wear and has been widely used in grinding [6,7] as well as in the machining with geometrically defined tools. Hase et al [8] monitored the AE signals when turning a mold steel (AISI O1) with cermet tools and correlated the signals with the cutting phenomena. They noticed that the chip formation process, the chip form and the primary shear angle affected significantly the AE signals.…”

A study to determine the onset of catastrophic wear of a processing tool by statistical parameters of acoustic emission

“…It is shown in [11] that when the tool wear occurs and develops, the energy spectrum of the AE signal changes, in which the low-frequency components prevail. AE energy during tool wear is studied in [12]. It is shown that with increasing wear of the processing tool, a non-linear increase in the stored energy of the AE signals occurs.…”

Intelligent Machining: Real-Time Tool Condition Monitoring and Intelligent Adaptive Control Systems

“…It should also ensure a reliable and robust tool pre-failure and failure indicator in a timely manner. Detecting the AE waves associated with the generation of new surfaces during unstable crack propagation in intermittent cutting is challenging due: (a) the nonlinearity of the generated AE signal, (b) the non-stationary nature of the stochastic unstable crack propagation process, (c) the contamination of the crack propagation bursts in the AE rms signal by the bursts coming from the force variation, chip formations, rubbing between the tool and workpiece, and the plastic deformation [29], and (d) the infinitesimal time spans of the high frequency bursts inherent in unstable crack propagation. This leaves a relatively short time (on millisecond-scale) for taking corrective actions after detection.…”