Online Machining Process Monitoring Using Wavelet Transform and SPC

A new online machining process monitoring system composing of several interconnected packages has been developed in LabVIEW environment. In this system, triggering and cross-correlation technique is introduced to align sensory signals acquired from different trials. The wavelet and short time Fourier transform is further explored to decompose sensory signals and extract features of tool malfunctions in machining processes. Univariate and multivariate statistical process monitoring techniques are proposed to construct the thresholds of free-malfunction machining zone. Experimental results obtained from the extensive broaching trials show that proposed techniques and monitoring system is effective to detect tool wear and construct thresholds