Analysis of acoustic emission signals and monitoring of machining processes

Advanced monitoring of machining operations

“…The use of single Fourier coefficients X[m] is not practical due to leakage effects. Thus, further SFs are usually considered: (i) amplitude of dominant spectral peaks [69,78,87,90,92,104]; (ii) signal power in specific frequency ranges [69,71,85,87,105,106]; (iii) energy in frequency bands [72,78,84]; (iv) statistic features of band power spectrum such as mean frequency, variance, skewness, kurtosis of the power spectrum distribution [87]; and (v) frequency of the spectrum highest peak [69,89,107].…”

“…Govekar et al [105] use filtered AE spectrum components for chip form classification. Kim and Ahn [82] propose a method of chip disposal state monitoring in drilling based on spindle motor power features.…”

Comparison and analysis of audible sound energy emissions during single point machining of HSTS with PVD TiCN cutter insert across full tool life

“…The research concluded that the energy of the acoustic emissions was affected by the degree of observed tool wear, and also that this varied based on the composition of the cutting insert. Govekar et al [16] analysed acoustic emission signals and the monitoring of machining processes and concluded that valuable information about the performance of the process can be gleaned from a correctly specified sensor configuration, a conclusion also reached by Tonshoff et al [17].…”

In-Line Spatial Monitoring of Cutting Tool-Wear

“…In indirect measuring techniques, toolwear is estimated using other more measurable machining pro-cess variables such as cutting force, acoustic emission, acceleration, energy consumption, etc. A survey of the literature indicates that many different approaches have been applied for tool-wear prediction [4][5][6][7][8]. Contrary, direct measuring techniques offer assessment of tool-wear by either evaluating the worn surface by optical methods (microscope).…”