A New Method for Detecting and Measuring Surface Wear

摘要

Monitoring of the machining process is essential in order to detect any undesired change in the machining environment and proceed to corrective actions. In this sense, early detection is crucial. A very important method is the analysis of surface wear during working process and on line detection of any significant changes in those signals. With this goal in mind we began in this paper with a method to characterize the wearing process of a steel material. The aim of the paper is to present a new method of wear measurement based on digital image processing. The image is converted into a two-dimensional set of signals and processed by means of selected filters, which includes the model of wavelet fuzzy neural network and the model of multivariate statistical analysis. The analysis of the digitized signals involves the wavelet theory.