Tool wear detection with fuzzy classification and wavelet fuzzy neural network
نویسندگان
چکیده
In the paper, a new method of tool wear detection with cutting conditions and detected signals is presented, which includes the model of wavelet fuzzy neural network with acoustic emission (AE) and the model of fuzzy classification with motor current. The results of tool wear estimated by cutting conditions and detected signals (spindle motor current, feed motor current and AE) are fused by fuzzy inference. Experimental results show that the method of tool wear detection is reliable and practical. 1999 Elsevier Science Ltd. All rights reserved.
منابع مشابه
Predictions of Tool Wear in Hard Turning of AISI4140 Steel through Artificial Neural Network, Fuzzy Logic and Regression Models
The tool wear is an unavoidable phenomenon when using coated carbide tools during hard turning of hardened steels. This work focuses on the prediction of tool wear using regression analysis and artificial neural network (ANN).The work piece taken into consideration is AISI4140 steel hardened to 47 HRC. The models are developed from the results of experiments, which are carried out based on De...
متن کاملA brief review: acoustic emission method for tool wear monitoring during turning
Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process monitoring. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing processes. This paper reviews briefly the research on AE sensing of tool ...
متن کاملThe use of wavelet - artificial neural network and adaptive neuro fuzzy inference system models to predict monthly precipitation
Precipitation forecasting due to its random nature in space and time always faced with many problems and this uncertainty reduces the validity of the forecasting model. Nowadays nonlinear networks as intelligent systems to predict such complex phenomena are widely used. One of the methods that have been considered in recent years in the fields of hydrology is use of wavelet transform as a moder...
متن کاملHigh impedance fault detection: Discrete wavelet transform and fuzzy function approximation
This paper presets a method including a combination of the wavelet transform and fuzzy function approximation (FFA) for high impedance fault (HIF) detection in distribution electricity network. Discrete wavelet transform (DWT) has been used in this paper as a tool for signal analysis. With studying different types of mother signals, detail types and feeder signal, the best case is selected. The...
متن کاملSUBCLASS FUZZY-SVM CLASSIFIER AS AN EFFICIENT METHOD TO ENHANCE THE MASS DETECTION IN MAMMOGRAMS
This paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. In this method, mammograms are segmented into regions of interest (ROI) in order to extract features including geometrical and contourlet coefficients. The extracted features benefit from...
متن کامل