CHARACTERISATION AND IDENTIFICATION OF DYNAMIC INSTABILITY IN MILLING OPERATION

Abstract Machining instability in the form of chatter is a physical process characterised by violent vibrations and extreme cutting force at the cutting point. The process has a very adverse impact on machine integrity, tool life, surface quality and dimensional accuracy and thus could significantly compromise productivity and manufacturing quality. A new approach effective for characterising the non-linear dynamic characteristics of the milling operation is described in this paper. Bifurcated states indicative of perturbed dynamic state from stability and the onset and progression of instability are unambiguously identified in the simultaneous time–frequency domain facilitated using the discrete wavelet transform (DWT). Results obtained through applying the approach to experimental milling force data demonstrate desired resolution over conventional methods in identifying the transition from a stable to unstable state. Because wavelets are closely related to filterbanks, the presented method can be applied to the real-time monitoring and optimisation of a large range of manufacturing processes.

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