Data stability and validity directly affect subsequent analysis and the determination of machining parameters in actual machining. Therefore, the real-time performance and stability of the presented synchronous dynamic data are extremely important technical indicators for evaluating the functionality of an intelligent toolholder.

During the research process, drilling operations were conducted under identical machining parameters using a piezoelectric sensor-based intelligent toolholder, a strain sensor-based intelligent toolholder, and the toolholder developed by our entity, namely iKIT wireless extrasensory toolholder. To facilitate data comparison, the tests for all three tool holders utilized new tools, specifically step drill bits with a diameter of 4.5-8 mm, and the spindle speed for drilling was uniformly set at 750 rpm.

For Piezoelectric sensor-based intelligent toolholder:

• While its sensitivity is indeed high, the extremely high sampling frequency during machining causes excessive data fluctuations, making it difficult for users to extract meaningful information and hindering subsequent analysis;
• Significant drift in Fz was observed before and after the experiment, amounting to approximately 7 N;

For Strain sensor-based intelligent toolholder:

• The baseline noise in the raw data is excessively high, with measurement processes affected by noise interference from the machine tool spindle drive system. The fluctuation ranges for Fz and M reach ±40 N and ±0.4 Nm, respectively. Users must perform smoothing or filtering to extract valid data, indicating significant uncertainty in data authenticity and measurement error.
• Significant Fz drift of up to 40 N was observed before and after the experiment;
• Excessive noise in Bx and By data obscured dynamic cutting changes, rendering the polar plot view non-referential.