Tool condition monitoring of aluminum oxide grinding wheel using AE and fuzzy model

Abstract

The grinding process is situated at the end of the machining chain, where geometric and dimensional characteristics and highquality surface are required. The constant use of cutting tool (grinding wheel) causes loss of its sharpness and clogging of the pores among the abrasive grains. In this context, the dressing operation is necessary to correct these and other problems related to its use in the process. Dressing is a reconditioning operation of the grinding wheel surface aiming at restoring the original condition and its efficiency. The objective of this study is to evaluate the surface regularity and dressing condition of the grinding wheel in the surface grinding process by means of digital signal processing of acoustic emission and fuzzy models. Tests were conducted by using synthetic diamond dressers in a surface grinding machine equipped with an aluminum oxide grinding wheel. The acoustic emission sensor was attached to the dresser holder. A frequency domain analysis was performed to choose the bands that best characterized the process. A frequency band of 25-40 kHz was used to calculate the ratio of power (ROP) statistic, and the mean and standard deviation values of the ROP were inputted to the fuzzy system. The results indicate that the fuzzy model was highly effective in diagnosing the surface conditions of the grinding wheel.

Acoustic Emission-Based Grinding Wheel Sharpness Monitoring Using Machine Learning Classifier

“…Nakayama et al [2] proposed a procedure for evaluating the abrasive wheel sharpness. Alexandre et al [3] proposed a test bench for measuring the sharpness of the abrasive wheel to study the dresser condition. In this study, the methodology proposed in [1,3] is used to design and fabricate the sharpness measurement device which is used to establish the conditions of the grinding wheel.…”

“…Off late, decision tree, Naive Bayes, SVM and artificial neural network models are used to predict the tool conditions in high-speed precision machining process [13][14][15]. In a surface grinding process, dresser conditions of aluminium oxide (Al 2 O 3 ) grinding wheel was studied by Alexandre et al [3] with AE and fuzzy methods.…”

A Contribution to the Monitoring of Ceramic Surface Quality Using a Low-Cost Piezoelectric Transducer in the Grinding Operation

“…One of the parameters that analyzes the frequency spectrum of acoustic emission signals is the ROP. This parameter addresses the power ratio of a given frequency band with the total power of the analyzed spectrum [8], which is defined in Equation (1).…”

Tool Condition Monitoring in Grinding Operation Using Piezoelectric Impedance and Wavelet Transform

“…Grinding operations are one of the most critical machining processes for manufacturing components that require high surface quality and precision. The effectiveness of the grinding process is significantly defined by the surface condition of the cutting tool (grinding wheel), and it is the dressing operation that is responsible for producing an appropriate topography for the grinding wheel [1][2][3]. In this sense, the condition monitoring of the dressing tool plays an essential role within grinding operations [4,5].…”