Gradual Deterioration Trending and Fault Diagnosis in Cutting Tools Using Inductive Inference Classification
نویسنده
چکیده
An effective procedure for the early detection and objective diagnosis of faults in turning machine cutting tools is described. The procedure involves the use of an inductive inference theory-based classification program called "Snob". The program objectively divides frequency spectra, generated from force measurements, into classes representing different cutting tool conditions. The estimated description length of each spectrum, which is used for classification, can also be used to detect the early stages of cutting tool deterioration. The procedure was tested using frequency spectra representing various stages of wear development in cutting tools during both accelerated wear rate and normal wear rate cutting tests. It is shown that the inductive inference theory-based spectra classification procedure allows early detection of cutting tool deterioration.
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