The data type default presented by the signals received from the iKIT wireless extrasensory toolholder is time-domain signals. If tool wear occurs, the frequency of the corresponding signals will shift. To analyze these changes and extract information regarding the tool wear state, it is necessary to convert the time-domain signals into the frequency domain via Fast Fourier Transform(FFT), thereby obtaining the frequency structure of the signals and the relationship between harmonic amplitudes and frequencies.

As illustrated in the experimental schematic, face milling tests were conducted on Al alloy. The wireless testing system synchronously monitors four force-related signals (F,M,B_x,B_y) and three-directional acceleration signals (X,Y,Z) in real-time. In this case, a sampling frequency of 512 Hz was employed for all seven sets of signals. The transmitted data signals are received via USB and transferred to the host computer software. The wireless testing system is capable of monitoring vibration signals during milling process. From the magnified view, the three-directional vibration signals all exhibit a'sine wave' pattern, indicating that the results are valid and conducive to machining analysis.

Simultaneously, the system can display real-time FFT plots for any data, where the X-axis represents frequency and the Y-axis represents amplitude. For real-time FFT analysis, users can select appropriate window functions according to practical needs, with options including Hamming, Hanning, and Boxcar. Upon completion of the data acquisition, users can select specific data segments for FFT analysis. As shown in the 'FFT Gauge' plot (X-axis: frequency; Y-axis: amplitude), the corresponding FFT results can be exported to facilitate subsequent plotting and tool wear analysis. Existing research has demonstrated that frequency-domain signals processed via FFT are instrumental in identifying the wear state of the tool.