Monitoring the wear of turning tools with the electromechanical impedance technique

Abstract

In this study, Inconel 718 and Ti6Al4V alloys were machined using ceramic (WG 300), and carbide (G20M Grade) inserts, respectively. The focused application was grooving. The tool wear was observed with traditional methods and with a new approach, the electromechanical impedance (EMI) technique. First, different machining durations were determined to obtain a different level of worn tools, and the wear amounts of tools were measured using a specialized optical microscope. Then, the electromechanical impedance signature of the new and worn tools was measured with two different piezoelectric sensors. It was understood that the wear level of the tools could also be determined with the EMI method. In order to evaluate the damage quantitatively, RMSD and CCD Damage Indexes (DI) were used. With this proposed method, it was thought that the tool wear level and the remaining machining time from the tool could be predicted with calculated DI. Additionally, a second study was conducted on irregularly worn carbide tools; it was understood that sensors location has a significant role in determining the wear zone; for the current setup, the flank wear could be detected more effectively with the EMI method than the wear on the rake side of the cutting tool.

Determination of the Dynamic Modulus of Elasticity of Pine Based on the PZT Transducer

“…Ritdumrongkul's research also showed that some peak frequencies in the real part of the EMI signal corresponded to the vibration modes of the beam coupled with a PZT patch [9]. For the small size, light weight, and high accuracy of the PZT patch, measurement and monitoring based on the EMI have been widely applied by many researchers, such as in damage monitoring [10,11], bolt connection monitoring [12,13], grinding process monitoring [14,15], wear monitoring [16,17], soil monitoring [18,19], and stress monitoring [20,21]. Carbajo and his research team have preliminarily investigated the feasibility of determining the elastic moduli of several kinds of materials based on the EMI response of the PZT patch for the first time [22].…”

Time-frequency analysis-based impulse feature extraction method for quantitative evaluation of milling tool wear

“…32,33 Monitoring tool wear during the machining process is of great significance, as it can affect the machining quality of the workpiece and pose a risk to workers when the cutting tool reaches a certain level of wear, the machining quality of the workpiece cannot be guaranteed and even bring danger to workers. 34,35 In this work, the cutting tool with different wear conditions is used to cut the workpiece, and the relevant vibration signal of the machining process is collected. Subsequently, the signal is processed by the GHST, and the energy proportion factor P of the periodic frequency point is defined to recognize the evaluation of tool wear.…”