| Central to creating a smart machining system is the challenge of collecting detailed information about the milling process at the tool tip. This work discusses the design, static calibration, dynamic characterization, and implementation of a low-cost wireless sensor for end-milling. Our novel strain-based sensor, called the Smart Tool, is shown to perform well in a laboratory setting with accuracy and dynamic behavior comparable to that of the Kistler 3-axis force dynamometer. The Smart Tool is capable of measuring static loads with a total measurement uncertainty of less than 3 percent full scale, but has a natural frequency of approximately 630 Hz. For this reason, signal conditioning of the strain signal is required when vibrations are large.;Several techniques in signal processing are investigated to show that the sensor is useful for force estimation, chatter prediction, force model calibration, and dynamic parameter identification. The presented techniques include a discussion of the Kalman filter and Weiner filter for signal enhancement, Linear Predictive Coding for system identification, model-based filtering for force estimation, and sub-optimal linear filters for removing forced vibrations. |
