Digital filtering techniques for processing signals utilized in the unmanned supervision of machinin

The application of digital filtering techniques is applied to the task of unmanned supervision of machining. Unmanned supervision of machining is desirable to free the operator from constantly overseeing the machining process and to expand his capability to detect in-process cutter breakage and control chatter. The filtering task is presented in two areas, the filtering of a time synchronous sound signal used in the detection of chatter, and filtering a rotation synchronous force or displacement signal in the detection of in-process cutter breakage.;In the area of filtering for the detection of chatter, the use and limitations of a revolution referenced finite impulse response comb filter is investigated. The issue of filter notch misplacement due to filtering the revolution synchronous signal utilizing a time based sampling is addressed, and system design parameters are established for a frequency range of interest versus sampling frequency. The performance of the filter during transient spindle speeds is also presented. Two alternative filtering techniques are investigated: an infinite impulse response comb and a high low pass comb filtering technique.;In the area of in-process cutter breakage, two filtering sub systems are presented. The first is based on a once per revolution difference comb filter to detect catastrophic in process breakage. The sub system utilizes a moving average filter to suppress signals during transient milling and has automatic thresholding. The second sub system is utilized to detect slowly progressing cutter damage and the existence of previous damage to the cutter. The sub system is designed to be insensitive to cutter run-out and relies on a calibration cut to establish threshold levels.